CN118014472A - Coal industry scheduling decision system based on big data analysis - Google Patents
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Abstract
The invention relates to the field of coal industry scheduling decision making, and particularly discloses a coal industry scheduling decision making system based on big data analysis.
Description
Technical Field
The invention relates to the field of coal industry scheduling decision making, in particular to a coal industry scheduling decision making system based on big data analysis.
Background
Coal transportation scheduling is one of important components of coal industry scheduling, and is to reasonably arrange time and path of coal transportation according to factors such as coal supply, demand and transportation distance so as to ensure that coal can be transported to a destination timely and efficiently.
In order to improve the transportation efficiency of coal transportation and reduce risks, a transportation scheduling scheme of multiple transportation modes in parallel is generally adopted, such as railway transportation, road transportation, water transportation and the like, the existing coal transportation scheduling is often used for adjusting the transportation scheduling plan in the implementation process of the transportation scheduling plan, namely, the transportation scheduling plan is timely adjusted after an emergency occurs in the transportation process, rather than pre-estimating possible risks of various transportation modes in advance before the transportation scheduling plan is implemented so as to adjust the scheduled transportation scheduling plan, so that the existing coal transportation scheduling is not changed from post-treatment to pre-intervention, and coal cannot be timely and efficiently transported to a destination and economic losses are easily caused.
Disclosure of Invention
Aiming at the problems, the invention provides a coal industry scheduling decision system based on big data analysis, which realizes the function of scheduling decisions for the coal industry.
The technical scheme adopted for solving the technical problems is as follows: the invention provides a coal industry scheduling decision system based on big data analysis, which comprises: the coal transportation plan information acquisition module: the method is used for acquiring basic information of various transportation modes from a coal production place to a transportation destination in a target coal enterprise coal transportation plan, and recording the basic information as basic information of various transportation modes in the coal transportation plan, wherein the basic information comprises transportation capacity, transportation path, transportation distance, predicted departure time and predicted arrival time, and the various transportation modes comprise railway transportation, road transportation and waterway transportation.
A coal railway transportation risk prediction module: the method is used for acquiring meteorological information and traffic information when coal arrives at each road section of a railway transportation path according to planned transportation, acquiring transportation information of each time of railway transportation in a history period, and analyzing risk coefficients of railway transportation in a coal transportation plan.
A coal highway transportation risk prediction module: the method is used for acquiring meteorological information and traffic information when coal arrives at each road section of a highway transportation path according to planned transportation, acquiring transportation information of each trip of transportation of the highway transportation path in a history period and analyzing risk coefficients of highway transportation in a coal transportation plan.
The coal waterway transportation risk prediction module comprises: the method is used for acquiring water conservancy information, meteorological information and traffic information when coal arrives at each road section of a waterway transportation path according to planned transportation, acquiring transportation information of each trip of the waterway transportation path history in a history period, and analyzing risk coefficients of waterway transportation in a coal transportation plan.
And a coal transportation plan adjustment judging module: the method is used for judging whether the coal transportation plan needs to be adjusted or not according to risk coefficients of railway transportation, road transportation and water transportation in the coal transportation plan, and feeding back the risk coefficients.
Database: the method is used for storing the transportation information of each transportation route of each transportation mode from the coal production place to the transportation destination in the history period, wherein the transportation information comprises the transportation capacity, the transportation loss amount, the delay time and the accident number.
On the basis of the embodiment, the concrete working process of the coal railway transportation risk prediction module comprises the following steps: dividing the transportation path of the railway transportation in the coal transportation plan according to a preset principle, obtaining each section of the transportation path of the railway transportation in the coal transportation plan, and marking the sections as each section of the railway transportation path.
And analyzing the time of coal to reach each section of the railway transportation path according to the planned transportation according to the transportation path, the transportation distance and the predicted departure time of the railway transportation in the coal transportation plan.
Further, through the meteorological department of the area where each section of the railway transportation path is located, the meteorological information when the coal arrives at each section of the railway transportation path according to the planned transportation is obtained, the air temperature, the air speed and the rainfall when the coal arrives at each section of the railway transportation path according to the planned transportation are obtained, and are respectively recorded as，/>Representing railway transportation route No. >The number of the individual road segments is set,。
By analysis of formulasObtaining the air temperature hidden danger factor/>, of the railway transportation pathWherein/>Correction coefficient representing preset air temperature hidden danger factor of railway transportation path,/>Indicating the preset proper air temperature of railway transportation,/>A deviation threshold value representing a preset railway transportation air temperature.
By analysis of formulasObtaining the wind speed hidden danger factor of the railway transportation pathWherein/>Correction coefficient representing preset potential wind speed factor of railway transportation path,/>And representing a preset wind speed early warning value of railway transportation.
Similarly, according to the analysis mode of the wind speed hidden danger factors of the railway transportation path, the rainfall hidden danger factors of the railway transportation path are obtained and are recorded as。
By analysis of formulasObtaining the meteorological hidden danger coefficient/>, of railway transportation in the coal transportation planWherein/>Correction factor representing preset meteorological hidden danger coefficient of railway transportation,/>Representing natural constant,/>Weights representing preset air temperature hidden danger factors, wind speed hidden danger factors and rainfall hidden danger factors,/>。
On the basis of the above embodiment, the specific working process of the coal railway transportation risk prediction module further includes: the traffic information when the coal arrives at each section of the railway transportation path according to the planned transportation is obtained through the traffic department of the area where each section of the railway transportation path is located, the predicted traffic amount when the coal arrives at each section of the railway transportation path according to the planned transportation is obtained and is recorded as。
By analysis of formulasObtaining the traffic hidden danger coefficient/>, of railway transportation in the coal transportation planWherein/>Correction factor representing preset potential railway transportation hazard coefficient,/>And representing a preset traffic quantity early warning value of railway transportation.
On the basis of the above embodiment, the specific working process of the coal railway transportation risk prediction module further includes: setting the duration of a history period, extracting the transportation information of each transportation route of each transportation mode from a coal production place to a transportation destination in the history period stored in a database, screening to obtain the transportation information of each transportation route corresponding to a railway transportation route from the coal production place to the transportation destination in the history period, recording the transportation information as the transportation information of each transportation route of the railway transportation route in the history period, obtaining the transportation capacity, the transportation loss amount, the delay duration and the accident number of each transportation route of the railway transportation route in the history period, and recording the transportation information as the transportation capacity, the transportation loss amount, the delay duration and the accident number of each transportation route of the railway transportation route in the history period respectively，/>Representing the history of the railway transportation path in the history period/>Number of the transportation,/>。
By analysis of formulasObtaining the historical transportation reliability coefficient/>, of railway transportation in coal transportation planningWherein/>Correction factor representing a predetermined historical shipping reliability coefficient for rail transportation,/>Representing the influence factor corresponding to the preset unit delay time length,/>And representing the influence factors corresponding to the number of the preset unit number of accidents.
On the basis of the above embodiment, the specific working process of the coal railway transportation risk prediction module further includes: the transportation capacity and the transportation distance of the railway transportation in the coal transportation plan are recorded asThe interval time between the estimated departure time and the estimated arrival time of the railway transportation in the coal transportation plan is obtained and is recorded as the transportation period of the railway transportation in the coal transportation plan and expressed as/>。
By analysis of formulasObtaining risk coefficient/>, of railway transportation in coal transportation planWherein/>Weights respectively representing preset weather hidden danger coefficients, traffic hidden danger coefficients and historical transportation reliability coefficients,/>，/>Correction quantity representing preset railway transportation risk coefficient,/>The preset thresholds of the transport capacity, transport distance, and transport period are respectively indicated.
On the basis of the above embodiment, the specific working process of the coal road transportation risk prediction module includes: d1: the method comprises the steps of obtaining weather information when coal arrives at each section of a highway transportation path according to planned transportation, obtaining weather types when the coal arrives at each section of the highway transportation path according to planned transportation, and further analyzing to obtain weather hidden danger coefficients of highway transportation in a coal transportation plan.
D2: and acquiring traffic information when the coal arrives at each section of the road transportation path according to the planned transportation, obtaining predicted traffic flow when the coal arrives at each section of the road transportation path according to the planned transportation, and further analyzing to obtain traffic hidden danger coefficients of the road transportation in the coal transportation plan.
D3: and acquiring transportation information of each transport trip of the road transportation path history in the history period, and obtaining the transportation capacity, the transportation loss, the delay time and the accident number of each transport trip of the road transportation path history in the history period, so as to further analyze the historical transportation reliability coefficient of the road transportation in the coal transportation plan.
On the basis of the above embodiment, the specific working process of the coal road transportation risk prediction module further includes: and acquiring the transportation capacity, the transportation distance and the transportation period of road transportation in the coal transportation plan.
And analyzing and obtaining the risk coefficient of the road transportation in the coal transportation plan according to the meteorological hidden danger coefficient, the traffic hidden danger coefficient, the historical transportation reliability coefficient, the transportation capacity, the transportation distance and the transportation period of the road transportation in the coal transportation plan.
On the basis of the above embodiment, the specific working process of the coal waterway transportation risk prediction module includes: f1: and acquiring water conservancy information and meteorological information when coal arrives at each section of the waterway transportation path according to the planned transportation, obtaining water level, wind speed and rainfall when the coal arrives at each section of the waterway transportation path according to the planned transportation, and further analyzing to obtain meteorological hidden danger coefficients of the waterway transportation in the coal transportation plan.
F2: the method comprises the steps of obtaining traffic information when coal arrives at each section of a waterway transportation path according to planned transportation, obtaining predicted traffic quantity when the coal arrives at each section of the waterway transportation path according to planned transportation, obtaining water channel width when the coal arrives at each section of the waterway transportation path according to planned transportation, and analyzing to obtain traffic hidden danger coefficients of the waterway transportation in the coal transportation plan.
F3: the method comprises the steps of obtaining transportation information of each trip of transportation of the water transportation path history in a history period, obtaining transportation capacity, transportation loss, delay time and accident times of each trip of transportation of the water transportation path history in the history period, and further analyzing historical transportation reliability coefficients of water transportation in a coal transportation plan.
On the basis of the above embodiment, the specific working process of the coal waterway transportation risk prediction module further includes: and acquiring the transportation capacity, the transportation distance and the transportation period of water road transportation in the coal transportation plan.
And analyzing and obtaining the risk coefficient of water road transportation in the coal transportation plan according to the meteorological hidden danger coefficient, the traffic hidden danger coefficient, the historical transportation reliability coefficient, the transportation capacity, the transportation distance and the transportation period of the water road transportation in the coal transportation plan.
Based on the above embodiment, the specific working process of the coal transportation plan adjustment and judgment module is as follows: and respectively comparing risk coefficients of railway transportation, road transportation and water transportation in the coal transportation plan with preset risk coefficient thresholds, if the risk coefficients of railway transportation, road transportation and water transportation in the coal transportation plan are smaller than the preset risk coefficient thresholds, the coal transportation plan does not need to be adjusted, otherwise, the coal transportation plan needs to be adjusted, further acquiring a transportation mode needing to be adjusted in the coal transportation plan, and feeding back to a target coal enterprise.
Compared with the prior art, the coal industry scheduling decision system based on big data analysis has the following beneficial effects: 1. according to the method, the risk coefficient of railway transportation in the coal transportation plan is analyzed by acquiring the meteorological information and the traffic information when coal is transported according to the plan to pass through the railway transportation path and the transportation information of the railway transportation path history, and the possible risk of railway transportation is estimated in advance before the transportation scheduling plan is implemented, so that the scheduled transportation scheduling plan is adjusted, the transportation risk is reduced to the maximum extent, the delay or loss of coal is avoided, the transportation efficiency is improved, and the coal is ensured to arrive at a destination in time.
2. According to the invention, the risk coefficient of the road transportation in the coal transportation plan is analyzed by acquiring the meteorological information and the traffic information when the coal is transported according to the plan to pass through the road transportation path and the transportation information of the road transportation path history, and the possible risk of the road transportation is estimated in advance before the transportation scheduling plan is implemented, so that the scheduled transportation scheduling plan is adjusted, thereby reducing the transportation risk to the maximum extent, avoiding causing delay or loss of the coal, improving the transportation efficiency and ensuring that the coal can arrive at the destination on time.
3. According to the method, the risk coefficient of water road transportation in the coal transportation plan is analyzed by acquiring water conservancy information, weather information and traffic information when coal is transported according to the plan to pass through a water road transportation path and transportation information of water road transportation path history; the possible risk of waterway transportation is estimated in advance before the transportation scheduling plan is implemented, and then the scheduled transportation scheduling plan is adjusted, so that the transportation risk is reduced to the maximum extent, delay or loss of coal is avoided, the transportation efficiency is improved, and the coal can arrive at a destination on time.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a diagram illustrating a system module connection according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the invention provides a coal industry scheduling decision system based on big data analysis, which comprises a coal transportation plan information acquisition module, a coal railway transportation risk prediction module, a coal road transportation risk prediction module, a coal waterway transportation risk prediction module, a coal transportation plan adjustment judgment module and a database.
The coal railway transportation risk prediction module is respectively connected with the coal transportation plan information acquisition module and the coal road transportation risk prediction module, the coal waterway transportation risk prediction module is respectively connected with the coal road transportation risk prediction module and the coal transportation plan adjustment judgment module, and the database is respectively connected with the coal railway transportation risk prediction module, the coal road transportation risk prediction module and the coal waterway transportation risk prediction module.
The coal transportation plan information acquisition module is used for acquiring basic information of various transportation modes from a coal production place to a transportation destination in a target coal enterprise coal transportation plan, and recording the basic information as basic information of various transportation modes in the coal transportation plan, wherein the basic information comprises transportation capacity, transportation path, transportation distance, predicted departure time and predicted arrival time, and the various transportation modes comprise railway transportation, road transportation and water route transportation.
As a preferable scheme, various transportation modes from a coal production place to a transportation destination in a target coal enterprise coal transportation plan are matched, namely railway transportation, road transportation and water transportation exist simultaneously, so that the transportation efficiency is improved, and the risk is reduced.
As a preferred embodiment, the transport distance represents the length of the transport path.
The coal railway transportation risk prediction module is used for acquiring weather information and traffic information when coal arrives at each road section of a railway transportation path according to planned transportation, acquiring transportation information of each trip of the railway transportation path in a history period and analyzing risk coefficients of railway transportation in a coal transportation plan.
Further, the concrete working process of the coal railway transportation risk prediction module comprises the following steps: dividing the transportation path of the railway transportation in the coal transportation plan according to a preset principle, obtaining each section of the transportation path of the railway transportation in the coal transportation plan, and marking the sections as each section of the railway transportation path.
As a preferred solution, the principle of dividing the transport path may be according to the principle of equidistant division or the principle of cross-regional division.
And analyzing the time of coal to reach each section of the railway transportation path according to the planned transportation according to the transportation path, the transportation distance and the predicted departure time of the railway transportation in the coal transportation plan.
As a preferable scheme, the time for coal to reach each section of a railway transportation path according to planned transportation is analyzed, and the concrete method comprises the following steps: according to the transportation path and the transportation distance of the railway transportation in the coal transportation plan, the distance of each section of the railway transportation path is obtained, the reference running speed of each section of the railway transportation path is set, the time required for passing through each section of the railway transportation path is further obtained, and the time for coal to reach each section of the railway transportation path according to the planned transportation is obtained by combining the predicted departure time of the railway transportation in the coal transportation plan.
Further, through the meteorological department of the area where each section of the railway transportation path is located, the meteorological information when the coal arrives at each section of the railway transportation path according to the planned transportation is obtained, the air temperature, the air speed and the rainfall when the coal arrives at each section of the railway transportation path according to the planned transportation are obtained, and are respectively recorded as，/>Representing railway transportation route No. >The number of the individual road segments is set,。
As a preferred option, extremely high or low temperatures can cause damage to railway lines and vehicles, thereby affecting coal railway transportation.
As a preferred solution, strong winds may affect the driving stability of the train and thus the coal rail transportation.
As a preferred solution, heavy rain may cause geological disasters or damage to railway lines, thereby affecting coal railway transportation.
By analysis of formulasObtaining the hidden air temperature factor of the railway transportation pathWherein/>Correction coefficient representing preset air temperature hidden danger factor of railway transportation path,/>Indicating the preset proper air temperature of railway transportation,/>A deviation threshold value representing a preset railway transportation air temperature.
As a preferable mode, the suitable air temperature for railway transportation is the median of the air temperature range suitable for railway transportation.
By analysis of formulasObtaining the wind speed hidden danger factor of the railway transportation pathWherein/>Correction coefficient representing preset potential wind speed factor of railway transportation path,/>And representing a preset wind speed early warning value of railway transportation.
Similarly, according to the analysis mode of the wind speed hidden danger factors of the railway transportation path, the rainfall hidden danger factors of the railway transportation path are obtained and are recorded as。
As a preferable scheme, the rainfall hidden danger factor of the railway transportation path is analyzed, and the specific method comprises the following steps: rainfall when coal arrives at each section of railway transportation path according to planned transportationSubstitution into analytical formulaObtaining rainfall hidden danger factor/>, of railway transportation pathWherein/>Correction coefficient representing preset rainfall hidden danger factor of railway transportation path,/>And representing a preset rainfall early warning value of railway transportation.
By analysis of formulasObtaining the meteorological hidden danger coefficient/>, of railway transportation in the coal transportation planWherein/>A correction factor representing a predetermined weather risk factor for the railway transportation,Representing natural constant,/>Weights representing preset air temperature hidden danger factors, wind speed hidden danger factors and rainfall hidden danger factors,/>。
Further, the concrete working process of the coal railway transportation risk prediction module further comprises the following steps: the traffic information when the coal arrives at each section of the railway transportation path according to the planned transportation is obtained through the traffic department of the area where each section of the railway transportation path is located, the predicted traffic amount when the coal arrives at each section of the railway transportation path according to the planned transportation is obtained and is recorded as。
As a preferable scheme, the method for obtaining the predicted traffic volume when coal arrives at each section of the railway transportation path according to the planned transportation comprises the following steps: and acquiring the traffic volume corresponding to the time when the coal arrives at each section of the railway transportation path according to the planned transportation in each historical year, and calculating the average value to obtain the predicted traffic volume when the coal arrives at each section of the railway transportation path according to the planned transportation.
As a preferred solution, the traffic volume of coal railway transportation has the characteristic of seasonal variation, for example, the traffic volume in winter may be increased and the traffic volume in summer may be reduced.
As a preferred solution, the traffic volume is the vehicle flow.
By analysis of formulasObtaining the traffic hidden danger coefficient/>, of railway transportation in the coal transportation planWherein/>Correction factor representing preset potential railway transportation hazard coefficient,/>And representing a preset traffic quantity early warning value of railway transportation.
Further, the concrete working process of the coal railway transportation risk prediction module further comprises the following steps: setting the duration of a history period, extracting the transportation information of each transportation route of each transportation mode from a coal production place to a transportation destination in the history period stored in a database, screening to obtain the transportation information of each transportation route corresponding to a railway transportation route from the coal production place to the transportation destination in the history period, recording the transportation information as the transportation information of each transportation route of the railway transportation route in the history period, obtaining the transportation capacity, the transportation loss amount, the delay duration and the accident number of each transportation route of the railway transportation route in the history period, and recording the transportation information as the transportation capacity, the transportation loss amount, the delay duration and the accident number of each transportation route of the railway transportation route in the history period respectively，/>Representing the history of the railway transportation path in the history period/>Number of the transportation,/>。
As a preferred aspect, the amount of loss in transportation represents the difference between the amount of coal loaded when it is sent out from the coal producing site and the amount of coal loaded when it reaches the transportation destination.
As a preferable mode, the delay time period means an interval time period between a time expected to reach the transportation destination and a time actually reaching the transportation destination.
By analysis of formulasObtaining the historical transportation reliability coefficient/>, of railway transportation in coal transportation planningWherein/>Correction factor representing a predetermined historical shipping reliability coefficient for rail transportation,/>Representing the influence factor corresponding to the preset unit delay time length,/>And representing the influence factors corresponding to the number of the preset unit number of accidents.
Further, the concrete working process of the coal railway transportation risk prediction module further comprises the following steps: the transportation capacity and the transportation distance of the railway transportation in the coal transportation plan are recorded asThe interval time between the estimated departure time and the estimated arrival time of the railway transportation in the coal transportation plan is obtained and is recorded as the transportation period of the railway transportation in the coal transportation plan and expressed as/>。
By analysis of formulasObtaining risk coefficient/>, of railway transportation in coal transportation planWherein/>Weights respectively representing preset weather hidden danger coefficients, traffic hidden danger coefficients and historical transportation reliability coefficients,/>，/>Correction quantity representing preset railway transportation risk coefficient,/>The preset thresholds of the transport capacity, transport distance, and transport period are respectively indicated.
The method and the system can analyze the risk coefficient of railway transportation in the coal transportation plan by acquiring the meteorological information and the traffic information when the coal is transported according to the plan to pass through the railway transportation path and the transportation information of the railway transportation path history, and pre-estimate the possible risk of the railway transportation before the transportation scheduling plan is implemented so as to adjust the pre-determined transportation scheduling plan, thereby reducing the transportation risk to the maximum extent, avoiding the delay or the loss of the coal, improving the transportation efficiency and ensuring that the coal can arrive at a destination in time.
The coal road transportation risk prediction module is used for acquiring meteorological information and traffic information when coal arrives at each road section of a road transportation path according to planned transportation, acquiring transportation information of each trip of transportation of the road transportation path in a history period and analyzing risk coefficients of road transportation in a coal transportation plan.
Further, the concrete working process of the coal road transportation risk prediction module comprises the following steps: d1: the method comprises the steps of obtaining weather information when coal arrives at each section of a highway transportation path according to planned transportation, obtaining weather types when the coal arrives at each section of the highway transportation path according to planned transportation, and further analyzing to obtain weather hidden danger coefficients of highway transportation in a coal transportation plan.
As a preferable scheme, the method for analyzing the meteorological hidden danger coefficient of road transportation in the coal transportation plan comprises the following steps: dividing the transportation path of the road transportation in the coal transportation plan according to a preset principle to obtain each section of the transportation path of the road transportation in the coal transportation plan, and marking the each section as each section of the road transportation path.
And analyzing the time of coal to reach each section of the highway transportation path according to the planned transportation according to the transportation path, the transportation distance and the predicted departure time of the highway transportation in the coal transportation plan.
And further acquiring weather information when the coal arrives at each section of the road transportation path according to the planned transportation by a weather department of the region where each section of the road transportation path is located, and acquiring the weather type when the coal arrives at each section of the road transportation path according to the planned transportation.
Setting hidden danger factors corresponding to each meteorological type, screening to obtain hidden danger factors corresponding to the meteorological types when coal arrives at each section of a highway transportation path according to planned transportation, and recording the hidden danger factors as，/>Express highway transportation route/>Number of individual road segment,/>。
By analysis of formulasObtaining the meteorological hidden danger coefficient/>, of road transportation in the coal transportation planWherein/>And the correction factor is used for representing the preset highway transportation weather hidden danger coefficient.
As a preferable scheme, the method for analyzing the time when coal arrives at each section of the road transportation path according to the planned transportation is the same as the method for analyzing the time when coal arrives at each section of the railway transportation path according to the planned transportation.
D2: and acquiring traffic information when the coal arrives at each section of the road transportation path according to the planned transportation, obtaining predicted traffic flow when the coal arrives at each section of the road transportation path according to the planned transportation, and further analyzing to obtain traffic hidden danger coefficients of the road transportation in the coal transportation plan.
As a preferable scheme, the method for obtaining the predicted traffic flow when the coal arrives at each section of the road transportation path according to the planned transportation is the same as the method for obtaining the predicted traffic flow when the coal arrives at each section of the railway transportation path according to the planned transportation.
As a preferable scheme, the method for analyzing the traffic risk coefficient of road transportation in the coal transportation plan is the same as the method for analyzing the traffic risk coefficient of railway transportation in the coal transportation plan in principle.
D3: and acquiring transportation information of each transport trip of the road transportation path history in the history period, and obtaining the transportation capacity, the transportation loss, the delay time and the accident number of each transport trip of the road transportation path history in the history period, so as to further analyze the historical transportation reliability coefficient of the road transportation in the coal transportation plan.
As a preferable scheme, the method for acquiring the transportation information of each trip of the road transportation path history in the history period is the same as the method for acquiring the transportation information of each trip of the railway transportation path history in the history period.
As a preferable scheme, the method for analyzing the historical transportation reliability coefficient of road transportation in the coal transportation plan is the same as the method for analyzing the historical transportation reliability coefficient of railway transportation in the coal transportation plan.
Further, the concrete working process of the coal road transportation risk prediction module further comprises the following steps: and acquiring the transportation capacity, the transportation distance and the transportation period of road transportation in the coal transportation plan.
And analyzing and obtaining the risk coefficient of the road transportation in the coal transportation plan according to the meteorological hidden danger coefficient, the traffic hidden danger coefficient, the historical transportation reliability coefficient, the transportation capacity, the transportation distance and the transportation period of the road transportation in the coal transportation plan.
As a preferable scheme, the method for analyzing the risk coefficient of road transportation in the coal transportation plan is the same as the method for analyzing the risk coefficient of railway transportation in the coal transportation plan.
The method and the system can analyze the risk coefficient of the road transportation in the coal transportation plan by acquiring the meteorological information and the traffic information when the coal is transported according to the plan to pass through the road transportation path and the transportation information of the road transportation path history, and pre-estimate the possible risk of the road transportation before the transportation scheduling plan is implemented so as to adjust the pre-determined transportation scheduling plan, thereby reducing the transportation risk to the maximum extent, avoiding the delay or the loss of the coal, improving the transportation efficiency and ensuring that the coal can arrive at the destination in time.
The coal waterway transportation risk prediction module is used for acquiring water conservancy information, weather information and traffic information when coal arrives at each road section of a waterway transportation path according to planned transportation, acquiring transportation information of each trip of transportation of the waterway transportation path history in a history period, and analyzing waterway transportation risk coefficients in a coal transportation plan.
Further, the concrete working process of the coal waterway transportation risk prediction module comprises the following steps: f1: and acquiring water conservancy information and meteorological information when coal arrives at each section of the waterway transportation path according to the planned transportation, obtaining water level, wind speed and rainfall when the coal arrives at each section of the waterway transportation path according to the planned transportation, and further analyzing to obtain meteorological hidden danger coefficients of the waterway transportation in the coal transportation plan.
As a preferable scheme, the method for analyzing the meteorological hidden danger coefficient of water route transportation in the coal transportation plan comprises the following steps: dividing the transportation path of water road transportation in the coal transportation plan according to a preset principle to obtain each section of the transportation path of water road transportation in the coal transportation plan, and marking the each section as each section of the water road transportation path.
And analyzing the time of coal to reach each section of the waterway transportation path according to the planned transportation according to the transportation path, the transportation distance and the predicted departure time of the waterway transportation in the coal transportation plan.
Further, through the water conservancy department and the meteorological department of the area where each section of the waterway transportation path is located, the water conservancy information and the meteorological information when the coal arrives at each section of the waterway transportation path according to the planned transportation are obtained, the water level, the wind speed and the rainfall when the coal arrives at each section of the waterway transportation path according to the planned transportation are obtained, and are respectively recorded as，/>Represents waterway transport route No. >Number of individual road segment,/>。
By analysis of formulasObtaining meteorological hidden danger coefficient/>, of water road transportation in coal transportation planWherein/>A correction factor representing a preset water route transportation weather hidden trouble coefficient,Representing a preset water level threshold,/>Respectively representing a preset wind speed early warning value and a rainfall threshold value of water transportation.
F2: the method comprises the steps of obtaining traffic information when coal arrives at each section of a waterway transportation path according to planned transportation, obtaining predicted traffic quantity when the coal arrives at each section of the waterway transportation path according to planned transportation, obtaining water channel width when the coal arrives at each section of the waterway transportation path according to planned transportation, and analyzing to obtain traffic hidden danger coefficients of the waterway transportation in the coal transportation plan.
As a preferable scheme, the method for analyzing the potential traffic hazard coefficient of water transportation in the coal transportation plan comprises the following steps: the traffic information when the coal arrives at each section of the waterway transportation path according to the planned transportation is obtained through the traffic department of the area where each section of the waterway transportation path is located, the predicted traffic amount when the coal arrives at each section of the waterway transportation path according to the planned transportation is obtained and is recorded asThe water channel width of coal when the coal arrives at each section of the water channel transportation path according to planned transportation is obtained through a satellite map and is recorded as/>。
By analysis of formulasObtaining the traffic hidden danger coefficient/>, of water road transportation in the coal transportation planWherein/>Correction factor representing preset water route transportation hidden danger coefficient,/>Representing preset traffic early warning value of water transportation,/>Indicating a preset waterway width threshold. /(I)
F3: the method comprises the steps of obtaining transportation information of each trip of transportation of the water transportation path history in a history period, obtaining transportation capacity, transportation loss, delay time and accident times of each trip of transportation of the water transportation path history in the history period, and further analyzing historical transportation reliability coefficients of water transportation in a coal transportation plan.
As a preferable scheme, the method for acquiring the transportation information of each trip of the water route transportation path history in the history period is the same as the method for acquiring the transportation information of each trip of the railway transportation path history in the history period.
As a preferable scheme, the method for analyzing the historical transportation reliability coefficient of the water route transportation in the coal transportation plan is the same as the method for analyzing the historical transportation reliability coefficient of the railway transportation in the coal transportation plan.
Further, the concrete working process of the coal waterway transportation risk prediction module further comprises the following steps: and acquiring the transportation capacity, the transportation distance and the transportation period of water road transportation in the coal transportation plan.
And analyzing and obtaining the risk coefficient of water road transportation in the coal transportation plan according to the meteorological hidden danger coefficient, the traffic hidden danger coefficient, the historical transportation reliability coefficient, the transportation capacity, the transportation distance and the transportation period of the water road transportation in the coal transportation plan.
As a preferable scheme, the method for analyzing the risk coefficient of water transportation in the coal transportation plan is the same as the method for analyzing the risk coefficient of railway transportation in the coal transportation plan.
The method is characterized in that the risk coefficient of water road transportation in the coal transportation plan is analyzed by acquiring water conservancy information, weather information and traffic information and transportation information of water road transportation path history when coal is transported according to the plan to pass through the water road transportation path; the possible risk of waterway transportation is estimated in advance before the transportation scheduling plan is implemented, and then the scheduled transportation scheduling plan is adjusted, so that the transportation risk is reduced to the maximum extent, delay or loss of coal is avoided, the transportation efficiency is improved, and the coal can arrive at a destination on time.
The coal transportation plan adjustment judging module is used for judging whether the coal transportation plan needs adjustment or not according to risk coefficients of railway transportation, road transportation and waterway transportation in the coal transportation plan, and feeding back the risk coefficients.
Further, the concrete working process of the coal transportation plan adjustment judging module is as follows: and respectively comparing risk coefficients of railway transportation, road transportation and water transportation in the coal transportation plan with preset risk coefficient thresholds, if the risk coefficients of railway transportation, road transportation and water transportation in the coal transportation plan are smaller than the preset risk coefficient thresholds, the coal transportation plan does not need to be adjusted, otherwise, the coal transportation plan needs to be adjusted, further acquiring a transportation mode needing to be adjusted in the coal transportation plan, and feeding back to a target coal enterprise.
As a preferred option, the adjustment of the transport mode in the coal transport plan can be to reduce the transport capacity, to change the transport path, to modify the estimated departure time or to change the transport mode.
The database is used for storing the transportation information of each transportation route of each transportation mode from the coal production place to the transportation destination in the history period, wherein the transportation information comprises the transportation capacity, the transportation loss amount, the delay time and the accident number.
The foregoing is merely illustrative and explanatory of the principles of this invention, as various modifications and additions may be made to the specific embodiments described, or similar arrangements may be substituted by those skilled in the art, without departing from the principles of this invention or beyond the scope of this invention as defined in the claims.
Claims (10)
1. The coal industry scheduling decision-making system based on big data analysis is characterized by comprising:
the coal transportation plan information acquisition module: the method comprises the steps of acquiring basic information of various transportation modes from a coal production place to a transportation destination in a target coal enterprise coal transportation plan, and recording the basic information as basic information of various transportation modes in the coal transportation plan, wherein the basic information comprises transportation capacity, transportation path, transportation distance, predicted departure time and predicted arrival time, and the various transportation modes comprise railway transportation, road transportation and waterway transportation;
A coal railway transportation risk prediction module: the method comprises the steps of acquiring meteorological information and traffic information when coal arrives at each road section of a railway transportation path according to planned transportation, acquiring transportation information of each time of railway transportation in a history period, and analyzing risk coefficients of railway transportation in a coal transportation plan;
A coal highway transportation risk prediction module: the method comprises the steps of acquiring meteorological information and traffic information when coal arrives at each road section of a highway transportation path according to planned transportation, acquiring transportation information of each trip of transportation of the highway transportation path in a history period, and analyzing risk coefficients of highway transportation in a coal transportation plan;
The coal waterway transportation risk prediction module comprises: the method comprises the steps of acquiring water conservancy information, weather information and traffic information when coal arrives at each road section of a waterway transportation path according to planned transportation, acquiring transportation information of each trip of transportation of the waterway transportation path in a history period, and analyzing risk coefficients of the waterway transportation in the coal transportation plan;
and a coal transportation plan adjustment judging module: the method is used for judging whether the coal transportation plan needs to be adjusted according to risk coefficients of railway transportation, road transportation and water transportation in the coal transportation plan and feeding back;
Database: the method is used for storing the transportation information of each transportation route of each transportation mode from the coal production place to the transportation destination in the history period, wherein the transportation information comprises the transportation capacity, the transportation loss amount, the delay time and the accident number.
2. The coal industry scheduling decision system based on big data analysis of claim 1, wherein: the concrete working process of the coal railway transportation risk prediction module comprises the following steps:
Dividing the transportation path of the railway transportation in the coal transportation plan according to a preset principle to obtain each section of the transportation path of the railway transportation in the coal transportation plan, and marking the sections as each section of the railway transportation path;
Analyzing the time of coal to reach each section of the railway transportation path according to the planned transportation according to the transportation path, transportation distance and predicted departure time of the railway transportation in the coal transportation plan;
Further, through the meteorological department of the area where each section of the railway transportation path is located, the meteorological information when the coal arrives at each section of the railway transportation path according to the planned transportation is obtained, the air temperature, the air speed and the rainfall when the coal arrives at each section of the railway transportation path according to the planned transportation are obtained, and are respectively recorded as ，/>Representing railway transportation route No. >The number of the individual road segments is set,；
By analysis of formulasObtaining the hidden air temperature factor of the railway transportation pathWherein/>Correction coefficient representing preset air temperature hidden danger factor of railway transportation path,/>Indicating the preset proper air temperature of railway transportation,/>A deviation threshold value representing a preset railway transportation air temperature;
By analysis of formulas Obtaining wind speed hidden danger factor/>, of railway transportation pathWherein/>Correction coefficient representing preset potential wind speed factor of railway transportation path,/>The method comprises the steps of representing a preset wind speed early warning value of railway transportation;
Similarly, according to the analysis mode of the wind speed hidden danger factors of the railway transportation path, the rainfall hidden danger factors of the railway transportation path are obtained and are recorded as ；
By analysis of formulasObtaining the meteorological hidden danger coefficient/>, of railway transportation in the coal transportation planWherein/>Correction factor representing preset meteorological hidden danger coefficient of railway transportation,/>Representing natural constant,/>Weights representing preset air temperature hidden danger factors, wind speed hidden danger factors and rainfall hidden danger factors,/>。
3. The coal industry scheduling decision system based on big data analysis of claim 2, wherein: the concrete working process of the coal railway transportation risk prediction module further comprises the following steps:
the traffic information when the coal arrives at each section of the railway transportation path according to the planned transportation is obtained through the traffic department of the area where each section of the railway transportation path is located, the predicted traffic amount when the coal arrives at each section of the railway transportation path according to the planned transportation is obtained and is recorded as ；
By analysis of formulasObtaining the traffic hidden danger coefficient/>, of railway transportation in the coal transportation planWherein/>Correction factor representing preset potential railway transportation hazard coefficient,/>And representing a preset traffic quantity early warning value of railway transportation.
4. The coal industry scheduling decision system based on big data analysis of claim 3, wherein: the concrete working process of the coal railway transportation risk prediction module further comprises the following steps:
Setting the duration of a history period, extracting the transportation information of each transportation route of each transportation mode from a coal production place to a transportation destination in the history period stored in a database, screening to obtain the transportation information of each transportation route corresponding to a railway transportation route from the coal production place to the transportation destination in the history period, recording the transportation information as the transportation information of each transportation route of the railway transportation route in the history period, obtaining the transportation capacity, the transportation loss amount, the delay duration and the accident number of each transportation route of the railway transportation route in the history period, and recording the transportation information as the transportation capacity, the transportation loss amount, the delay duration and the accident number of each transportation route of the railway transportation route in the history period respectively ，/>Representing the history of the railway transportation path in the history period/>Number of the transportation,/>；
By analysis of formulasObtaining the historical transportation reliability coefficient/>, of railway transportation in coal transportation planningWherein/>A correction factor representing a historical shipping reliability coefficient for a predetermined railroad shipment,Representing the influence factor corresponding to the preset unit delay time length,/>And representing the influence factors corresponding to the number of the preset unit number of accidents.
5. The coal industry scheduling decision system based on big data analysis of claim 4, wherein: the concrete working process of the coal railway transportation risk prediction module further comprises the following steps:
the transportation capacity and the transportation distance of the railway transportation in the coal transportation plan are recorded as The interval time between the estimated departure time and the estimated arrival time of the railway transportation in the coal transportation plan is obtained and is recorded as the transportation period of the railway transportation in the coal transportation plan and expressed as/>；
By analysis of formulasObtaining risk coefficient/>, of railway transportation in coal transportation planWherein/>Weights respectively representing preset weather hidden danger coefficients, traffic hidden danger coefficients and historical transportation reliability coefficients,/>，/>Correction quantity representing preset railway transportation risk coefficient,/>The preset thresholds of the transport capacity, transport distance, and transport period are respectively indicated.
6. The coal industry scheduling decision system based on big data analysis of claim 5, wherein: the concrete working process of the coal road transportation risk prediction module comprises the following steps:
D1: acquiring meteorological information when coal arrives at each section of a highway transportation path according to planned transportation, acquiring meteorological types when the coal arrives at each section of the highway transportation path according to planned transportation, and further analyzing to acquire meteorological hidden danger coefficients of highway transportation in a coal transportation plan;
D2: acquiring traffic information when coal arrives at each section of a highway transportation path according to planned transportation, obtaining predicted traffic flow when the coal arrives at each section of the highway transportation path according to planned transportation, and further analyzing to obtain traffic hidden danger coefficients of highway transportation in a coal transportation plan;
D3: and acquiring transportation information of each transport trip of the road transportation path history in the history period, and obtaining the transportation capacity, the transportation loss, the delay time and the accident number of each transport trip of the road transportation path history in the history period, so as to further analyze the historical transportation reliability coefficient of the road transportation in the coal transportation plan.
7. The coal industry scheduling decision system based on big data analysis of claim 6, wherein: the concrete working process of the coal road transportation risk prediction module further comprises the following steps:
Acquiring the transportation capacity, the transportation distance and the transportation period of road transportation in a coal transportation plan;
And analyzing and obtaining the risk coefficient of the road transportation in the coal transportation plan according to the meteorological hidden danger coefficient, the traffic hidden danger coefficient, the historical transportation reliability coefficient, the transportation capacity, the transportation distance and the transportation period of the road transportation in the coal transportation plan.
8. The coal industry scheduling decision system based on big data analysis of claim 5, wherein: the concrete working process of the coal waterway transportation risk prediction module comprises the following steps:
F1: acquiring water conservancy information and meteorological information when coal arrives at each section of a waterway transportation path according to planned transportation, obtaining water level, wind speed and rainfall when the coal arrives at each section of the waterway transportation path according to planned transportation, and further analyzing to obtain meteorological hidden danger coefficients of the waterway transportation in the coal transportation plan;
F2: acquiring traffic information when coal arrives at each section of a waterway transportation path according to planned transportation, acquiring predicted traffic quantity when coal arrives at each section of the waterway transportation path according to planned transportation, acquiring water channel width when coal arrives at each section of the waterway transportation path according to planned transportation, and analyzing to acquire traffic hidden danger coefficients of the waterway transportation in the coal transportation plan;
F3: the method comprises the steps of obtaining transportation information of each trip of transportation of the water transportation path history in a history period, obtaining transportation capacity, transportation loss, delay time and accident times of each trip of transportation of the water transportation path history in the history period, and further analyzing historical transportation reliability coefficients of water transportation in a coal transportation plan.
9. The coal industry scheduling decision system based on big data analysis of claim 8, wherein: the concrete working process of the coal waterway transportation risk prediction module further comprises the following steps:
acquiring the transportation capacity, the transportation distance and the transportation period of water road transportation in a coal transportation plan;
And analyzing and obtaining the risk coefficient of water road transportation in the coal transportation plan according to the meteorological hidden danger coefficient, the traffic hidden danger coefficient, the historical transportation reliability coefficient, the transportation capacity, the transportation distance and the transportation period of the water road transportation in the coal transportation plan.
10. The coal industry scheduling decision system based on big data analysis of claim 1, wherein: the concrete working process of the coal transportation plan adjustment judging module is as follows:
And respectively comparing risk coefficients of railway transportation, road transportation and water transportation in the coal transportation plan with preset risk coefficient thresholds, if the risk coefficients of railway transportation, road transportation and water transportation in the coal transportation plan are smaller than the preset risk coefficient thresholds, the coal transportation plan does not need to be adjusted, otherwise, the coal transportation plan needs to be adjusted, further acquiring a transportation mode needing to be adjusted in the coal transportation plan, and feeding back to a target coal enterprise.
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