CN112735095A - Natural disaster early warning system and method based on network - Google Patents
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Abstract
The invention discloses a natural disaster monitoring and early warning system and method based on a network. The system comprises: the system comprises a knowledge base, a network information acquisition and processing module, a threat early warning module and a response module; the network information acquisition processing module is used for acquiring first meteorological information data in a first preset time from a network, and comparing the first meteorological information data with the risk model in the knowledge base to obtain a meteorological matching result; and the response module acquires the corresponding meteorological response data in the knowledge base according to the meteorological matching result to obtain a response and precaution control strategy. Thereby realized the collection of network meteorological information and improved information acquisition coverage, realized the comparison of the meteorological information of collection and historical meteorological data simultaneously to obtain future meteorological type prediction and meteorological matching result according to the comparison result, accomplish to early warn and guard against in advance, thereby reduce the influence of natural disasters to social life.
Description
Technical Field
The embodiment of the invention relates to a natural disaster monitoring and early warning technology, in particular to a natural disaster monitoring and early warning system and method based on a network.
Background
With the continuous development of communication technology and computer network technology and the continuous progress of social economy, the information technology influences the aspects of people's life, and the utilization of the information technology to early warn natural disasters has important significance in reducing the influence of the natural disasters on social life.
In the equipment adopting intelligent information monitoring, specific components are mostly monitored and early warned at present. Although warning can be given on general and detailed problems, the coverage is limited. Early warning can not be carried out more comprehensively and more quickly under the condition of natural disasters, and the precaution work is well carried out.
Disclosure of Invention
The invention provides a natural disaster early warning system and a natural disaster early warning method based on a network, which realize the acquisition of network meteorological information so as to improve the information acquisition coverage, and simultaneously realize the comparison of the acquired meteorological information and historical meteorological data so as to obtain future meteorological type prediction and meteorological matching results according to the comparison result, realize early warning and early prevention, and further reduce the influence of natural disasters on social life.
In a first aspect, an embodiment of the present invention provides a natural disaster early warning system based on a network, including: the system comprises a knowledge base, a network information acquisition and processing module, a threat early warning module and a response module;
the knowledge base is used for storing a risk model;
the network information acquisition and processing module is connected with the threat early warning module and the knowledge base, and is used for acquiring first meteorological information data within first preset time from a network, comparing the first meteorological information data with the risk model in the knowledge base to obtain a meteorological matching result, and sending the meteorological matching result to the threat early warning module;
the knowledge base is also used for storing the first meteorological information data and meteorological corresponding data;
the threat early warning module is connected with the response module and used for displaying the matching result to a user and sending the weather matching result to the response module when receiving confirmation information input by the user;
the response module is connected with the knowledge base and used for receiving the weather matching result, acquiring corresponding weather coping data in the knowledge base according to the weather matching result to obtain a response and precaution control strategy and sending the response and precaution control strategy to the threat early warning module;
the threat early warning module is also used for displaying the response and precautionary control strategy.
Optionally, the network information acquisition processing module includes a data mining technology unit and a data analysis and comparison unit;
the data mining technical unit is used for mining network information and screening to obtain the first meteorological information data;
the data analysis and comparison unit is used for comparing the first meteorological information data with the risk model to obtain the meteorological matching result.
Optionally, the early warning system further comprises a monitoring module;
the monitoring module is used for monitoring meteorological data related to the meteorological matching result according to the meteorological matching result to obtain meteorological monitoring data and sending the meteorological monitoring data to the network information acquisition and processing module;
and the network information acquisition processing module is used for confirming the weather matching result according to the weather monitoring data and the risk model.
Optionally, the risk model comprises a conventional meteorological model and an unconventional meteorological model;
the data analysis and comparison unit is used for comparing the first meteorological information data with the risk model, and comparing the first meteorological information data with the unconventional meteorological model to obtain the meteorological matching result if the first meteorological information data exceeds the early warning threshold of the conventional meteorological model.
Optionally, the network information collecting and processing module is further configured to obtain second meteorological information data within a second preset time, and generate the risk model according to the second meteorological information data.
In a second aspect, an embodiment of the present invention provides a natural disaster early warning method based on a network, which is executed by an early warning system, where the system includes a knowledge base, a network information acquisition and processing module, a threat early warning module, and a response module; the network information acquisition and processing module is connected with the threat early warning module and the knowledge base, the threat early warning module is connected with the response module, and the response module is connected with the knowledge base;
the method comprises the following steps:
the knowledge base stores a risk model;
the network information acquisition processing module acquires first meteorological information data in first preset time from a network, compares the first meteorological information data with the risk model in the knowledge base to obtain a meteorological matching result, and sends the meteorological matching result to the threat early warning module;
the knowledge base stores the first meteorological information data and meteorological corresponding data;
the threat early warning module displays the matching result to a user and sends the weather matching result to a response module when receiving confirmation information input by the user;
the response module receives the weather matching result, acquires corresponding weather handling data in the knowledge base according to the weather matching result to obtain a response and precaution control strategy, and sends the response and precaution control strategy to the threat early warning module;
and the threat early warning module also displays the response and precaution control strategy.
Optionally, the network information acquisition processing module includes a data mining technology unit and a data analysis and comparison unit;
the method further comprises the step of enabling the user to select the target,
the data mining technical unit mines network information and screens to obtain the first meteorological information data;
and the data analysis and comparison unit compares the first meteorological information data with the risk model to obtain the meteorological matching result.
Optionally, the early warning system further includes a monitoring module;
the method further comprises the step of enabling the user to select the target,
the monitoring module monitors meteorological data related to the meteorological matching result according to the meteorological matching result to obtain meteorological monitoring data, and sends the meteorological monitoring data to the network information acquisition and processing module;
and the network information acquisition processing module confirms the weather matching result according to the weather monitoring data and the risk model.
Optionally, the risk model comprises a conventional meteorological model and an unconventional meteorological model;
the method further comprises the step of enabling the user to select the target,
and the data analysis and comparison unit compares the first meteorological information data with the risk model, and if the first meteorological information data exceeds an early warning threshold value of a conventional meteorological model, the first meteorological information data is compared with an unconventional meteorological model to obtain a meteorological matching result.
Optionally, the network information acquisition processing module acquires the second meteorological information data within a second preset time, and generates the risk model according to the second meteorological information data.
The natural disaster early warning system and method based on the network provided by the embodiment of the invention acquire network meteorological information through the network information acquisition processing module and compare the network meteorological information with the risk model to generate a meteorological matching result, and utilize the meteorological matching result to output a response and precaution control strategy. Thereby realized the collection of network meteorological information and improved information acquisition coverage, realized the comparison of the meteorological information of collection and historical meteorological data simultaneously to obtain future meteorological type prediction and meteorological matching result according to the comparison result, accomplish to early warn and guard against in advance, thereby reduce the influence of natural disasters to social life.
Drawings
Fig. 1 is a schematic structural diagram of a natural disaster early warning system based on a network according to an embodiment of the present invention.
Fig. 2 is a schematic structural diagram of another network-based natural disaster early warning system according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic structural diagram of a natural disaster early warning system based on a network according to an embodiment of the present invention, and referring to fig. 1, the early warning system includes: the system comprises a knowledge base 120, a network information acquisition and processing module 110, a threat early warning module 130 and a response module 140;
the knowledge base 120 is used to store risk models;
the network information acquisition processing module 110 is connected with the threat early warning module 130 and the knowledge base 120, and the network information acquisition processing module 110 is configured to acquire first weather information data within a first preset time from a network, compare the first weather information data with a risk model in the knowledge base 120 to obtain a weather matching result, and send the weather matching result to the threat early warning module 130;
the knowledge base 120 is further used for storing first meteorological information data and meteorological corresponding data;
the threat early warning module 130 is connected with the response module 140, and the threat early warning module 130 is used for displaying the matching result to the user and sending the weather matching result to the response module 140 when receiving the confirmation information input by the user;
the response module 140 is connected to the knowledge base 120, and is configured to receive the weather matching result, obtain corresponding weather handling data in the knowledge base 120 according to the weather matching result, obtain a response and precaution control policy, and send the response and precaution control policy to the threat early warning module 130;
the threat early warning module 130 is also used to present response and precautionary control strategies.
Specifically, the first preset time refers to a middle-short period of time in the region, and may be a certain period of time from one week to six months. The first weather information data refers to region data, time, place, temperature, wind power size, relative humidity, weather condition and other information. Knowing historical meteorological data of natural disasters occurring in the early stage of a certain area, establishing a risk model and storing the risk model in the knowledge base 120. The network information acquisition processing module 110 acquires the first meteorological information data in the region in a short time, and the first meteorological information data is compared and matched with the data in the risk model to confirm the meteorological matching result of the first meteorological information data. And when the data fluctuation difference value in the first meteorological information data exceeds an early warning threshold value in the risk model, comparing and matching the risk model with the risk category model in the risk model to obtain a meteorological matching result. For example, if the data fluctuation of the humidity data in the first weather information data exceeds the early warning threshold of the risk model, the first weather information data is compared with the risk models included in the risk model one by one and matched with the risk models corresponding to the rainstorm risk types, and the weather matching result is the rainstorm weather result. The weather matching result comprises weather types, disaster type data and a time table which provides future weather types through variable analysis prediction in the time period of the area, wherein the time table refers to a reoccurrence time period predicted by a variable calculation method. The threat early warning module 130 receives the weather matching result and displays the weather matching result to the user, and the user can correct and calibrate the weather matching result according to the display result and the weather rule defined by the user. The user defines a rule that is artificially defined, and due to the influence of different environmental factors caused by various conditions of various regions, the early warning threshold value of the system needs to be adjusted and updated, and if the matching result is a potentially threatening event, the early warning threshold value needs to be artificially judged whether the data is reasonable or not rather than abnormal. After the user confirms, the response module 140 calls the image response data in the knowledge base 120 to generate a response and precaution control strategy, and the threat early warning module 130 may present the response and precaution control strategy to the user. The system can widely provide timely prevention for reoccurrence of natural weather or disasters, and loss is reduced.
The natural disaster early warning system based on the network provided by the embodiment of the invention acquires the network meteorological information through the network information acquisition processing module and compares the network meteorological information with the risk model to generate a meteorological matching result, and outputs a response and precaution control strategy by using the meteorological matching result. Thereby realized the collection of network meteorological information and improved information acquisition coverage, realized the comparison of the meteorological information of collection and historical meteorological data simultaneously to obtain future meteorological type prediction and meteorological matching result according to the comparison result, accomplish to early warn and guard against in advance, thereby reduce the influence of natural disasters to social life.
Fig. 2 is a schematic structural diagram of another network-based natural disaster early warning system according to an embodiment of the present invention, referring to fig. 2, optionally, the network information collecting and processing module includes a data mining technology unit 111 and a data analysis and comparison unit 112;
the data mining technology unit 111 is used for mining network information and screening to obtain first meteorological information data;
the data analysis and comparison unit 112 is configured to compare the first weather information data with the risk model to obtain a weather matching result.
Based on the above embodiment, specifically, the data mining technology unit 111 uses a calendar, and the main idea is to first obtain all URL addresses of the next layer based on a given URL according to a custom rule, and then continuously move down until all contents of HTML pages that meet the rule are obtained. Where a given URL is the root node of a number. Based on a given URL, acquiring a root node of a tree, namely a first layer with breadth first, acquiring three URL link addresses of a second layer by combining a customized rule through analyzing the content of an HTML webpage, then saving the three URL link addresses into a CrawDB of a Web Collector framework, and setting the state values of the three URL link addresses to be 0, namely not grabbing. The state value of the root node is then set to 1 in the CrawlDB, i.e., has been crawled. And repeating the crawling process of the first layer, respectively capturing the stored three URL link addresses to obtain corresponding HTML webpage content, then acquiring the URL address of the third layer by combining rules, simultaneously storing the analyzed new URL address into a CrawDB, setting the state value of the new URL address to be 0, and then setting the state values of the three leaf nodes of the second layer to be 1. And by analogy, the leaf nodes are crawled until the leaf nodes are the boundaries set by the rules, namely the set crawling layer number or a certain exit rule, and then all the analyzed HTML webpage contents are traversed, and the needed data are searched and stored. The web crawler is used for automatically extracting the web content program, so that the web crawler can autonomously browse the web and actively crawl the web content according to the rule. And analyzing and sorting the automatically collected page contents according to a certain rule through the acquired website contents and the retrieval mode thereof. The working principle is that starting from a URLS list, namely, unified resource addresses are uniformly stored in a list to be accessed for subsequent arrangement and application; according to key phrases about weather, environment and the like, the crawler system is used for continuously accessing and copying found required contents into a mysql database for viewing and calling.
The data analysis and comparison unit 112 firstly classifies the data obtained by the network into meteorological information data by using a K-Means clustering algorithm. And comparing the weather matching result with the risk model to obtain a weather matching result. For the K-Means algorithm, namely, K cluster centers are given at random initially, and sample points to be classified are classified into clusters according to the nearest neighbor principle. And then, the centroid of each cluster is recalculated according to an averaging method, so that a new cluster center is determined. And iterating until the moving distance of the cluster center is smaller than a given value, namely the similarity measure, and adopting a sum of squared errors criterion function as a clustering criterion function.
With continued reference to fig. 2, based on the foregoing embodiment, optionally, the early warning system further includes a monitoring module 210;
the monitoring module 210 is configured to monitor weather data related to the weather matching result according to the weather matching result to obtain weather monitoring data, and send the weather monitoring data to the network information acquisition and processing module;
the network information collecting and processing module 110 is used for confirming the weather matching result according to the weather monitoring data and the risk model.
Specifically, the external monitoring device can be used as the monitoring module 210, the monitoring device can select a micro meteorological sensor, an automatic meteorological station, a high-precision distance meter and the like, according to the meteorological matching result, the monitoring device continues to monitor the meteorological information data of the result for a certain time, and sends the meteorological monitoring data to the network information acquisition and processing module. And the network information acquisition processing module compares and analyzes the meteorological monitoring data with the risk model in real time, and confirms or updates and corrects the meteorological matching result.
Optionally, the risk model comprises a conventional meteorological model and an unconventional meteorological model;
the data analysis and comparison unit is used for comparing the first meteorological information data with the risk model, and if the first meteorological information data exceeds the early warning threshold value of the conventional meteorological model, comparing the first meteorological information data with the unconventional meteorological model to obtain a meteorological matching result.
Specifically, the conventional meteorological model is a general wind, rain and snow weather model, and the unconventional meteorological model includes a mountain fire model, a flood model, a typhoon model, a seismic model, a debris flow model, a drought model, a high-temperature model, a cold model and a lightning stroke model. The data analysis and comparison unit firstly compares the region data, time, place, temperature, wind power size, relative humidity, meteorological conditions and other information in the first meteorological information data with the conventional meteorological model, and when the data fluctuation difference value in the first meteorological information data does not exceed the early warning threshold value in the conventional meteorological model, a meteorological matching result is obtained in the conventional meteorological model. And if one or more data fluctuation difference values in the first meteorological information data exceed the early warning threshold value in the conventional meteorological model, continuously comparing with the unconventional meteorological model and obtaining a meteorological matching result.
Optionally, the network information acquisition processing module is further configured to acquire second meteorological information data within a second preset time, and generate a risk model according to the second meteorological information data.
Specifically, the network information acquisition processing module acquires second meteorological information data in the region for a long time, and the second meteorological information data performs meteorological information data classification on the data by using a K-Means clustering algorithm. And generating a risk model according to the second meteorological information data and the meteorological type. The long term time may be a period of time in years, such as a long term time of 3 years, 5 years, or 10 years. The second meteorological information data includes domain data, time, place, temperature, wind size, relative humidity, meteorological conditions, and the like.
The embodiment of the invention provides a natural disaster early warning method based on a network, which is executed by an early warning system, wherein the system comprises a knowledge base, a network information acquisition and processing module, a threat early warning module and a response module; the network information acquisition processing module is connected with the threat early warning module and the knowledge base, the threat early warning module is connected with the response module, and the response module is connected with the knowledge base;
the method comprises the following steps:
the knowledge base stores a risk model;
the network information acquisition processing module acquires first meteorological information data in first preset time from a network, compares the first meteorological information data with a risk model in a knowledge base to obtain a meteorological matching result, and sends the meteorological matching result to the threat early warning module;
the knowledge base stores first meteorological information data and meteorological corresponding data;
the threat early warning module displays the matching result to a user and sends the weather matching result to the response module when receiving confirmation information input by the user;
the response module receives the weather matching result, acquires corresponding weather coping data in the knowledge base according to the weather matching result to obtain a response and precaution control strategy, and sends the response and precaution control strategy to the threat early warning module;
the threat early warning module also displays a response and precaution control strategy.
Optionally, the network information acquisition processing module includes a data mining technology unit and a data analysis and comparison unit;
the method further comprises the step of carrying out,
the data mining technical unit mines network information and screens to obtain first meteorological information data;
and the data analysis and comparison unit compares the first meteorological information data with the risk model to obtain a meteorological matching result.
Optionally, the early warning system further comprises a monitoring module;
the method further comprises the step of carrying out,
the monitoring module monitors meteorological data related to the meteorological matching result according to the meteorological matching result to obtain meteorological monitoring data, and sends the meteorological monitoring data to the network information acquisition processing module;
and the network information acquisition processing module confirms the weather matching result according to the weather monitoring data and the risk model.
Optionally, the risk model comprises a conventional meteorological model and an unconventional meteorological model;
the method further comprises the step of carrying out,
and the data analysis and comparison unit compares the first meteorological information data with the risk model, and if the first meteorological information data exceeds the early warning threshold value of the conventional meteorological model, the first meteorological information data is compared with the unconventional meteorological model to obtain a meteorological matching result.
Optionally, the network information acquisition processing module acquires second meteorological information data within a second preset time, and generates a risk model according to the second meteorological information data.
The natural disaster early warning method based on the network provided by the embodiment of the invention and the natural disaster early warning system based on the network provided by any embodiment of the invention belong to the same inventive concept, have corresponding beneficial effects, and the detailed technical details in the embodiment are not shown in the natural disaster early warning system based on the network provided by any embodiment of the invention.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A natural disaster early warning system based on network, characterized by comprising: the system comprises a knowledge base, a network information acquisition and processing module, a threat early warning module and a response module;
the knowledge base is used for storing a risk model;
the network information acquisition and processing module is connected with the threat early warning module and the knowledge base, and is used for acquiring first meteorological information data within first preset time from a network, comparing the first meteorological information data with the risk model in the knowledge base to obtain a meteorological matching result, and sending the meteorological matching result to the threat early warning module;
the knowledge base is also used for storing the first meteorological information data and meteorological corresponding data;
the threat early warning module is connected with the response module and used for displaying the matching result to a user and sending the weather matching result to the response module when receiving confirmation information input by the user;
the response module is connected with the knowledge base and used for receiving the weather matching result, acquiring corresponding weather coping data in the knowledge base according to the weather matching result to obtain a response and precaution control strategy and sending the response and precaution control strategy to the threat early warning module;
the threat early warning module is also used for displaying the response and precautionary control strategy.
2. A network-based natural disaster early warning system as claimed in claim 1, wherein:
the network information acquisition processing module comprises a data mining technology unit and a data analysis comparison unit;
the data mining technical unit is used for mining network information and screening to obtain the first meteorological information data;
the data analysis and comparison unit is used for comparing the first meteorological information data with the risk model to obtain the meteorological matching result.
3. A network-based natural disaster early warning system according to claim 2, wherein: the monitoring system also comprises a monitoring module;
the monitoring module is used for monitoring meteorological data related to the meteorological matching result according to the meteorological matching result to obtain meteorological monitoring data and sending the meteorological monitoring data to the network information acquisition and processing module;
and the network information acquisition processing module is used for confirming the weather matching result according to the weather monitoring data and the risk model.
4. A network-based natural disaster early warning system according to claim 2, wherein:
the risk models comprise a conventional meteorological model and an unconventional meteorological model;
the data analysis and comparison unit is used for comparing the first meteorological information data with the risk model, and comparing the first meteorological information data with the unconventional meteorological model to obtain the meteorological matching result if the first meteorological information data exceeds the early warning threshold of the conventional meteorological model.
5. The network-based natural disaster early warning system of claim 4, wherein:
the network information acquisition processing module is further configured to acquire the second meteorological information data within a second preset time, and generate the risk model according to the second meteorological information data.
6. A natural disaster early warning method based on network is executed by an early warning system, and is characterized in that the system comprises a knowledge base, a network information acquisition and processing module, a threat early warning module and a response module; the network information acquisition and processing module is connected with the threat early warning module and the knowledge base, the threat early warning module is connected with the response module, and the response module is connected with the knowledge base;
the method comprises the following steps:
the knowledge base stores a risk model;
the network information acquisition processing module acquires first meteorological information data in first preset time from a network, compares the first meteorological information data with the risk model in the knowledge base to obtain a meteorological matching result, and sends the meteorological matching result to the threat early warning module;
the knowledge base stores the first meteorological information data and meteorological corresponding data;
the threat early warning module displays the matching result to a user and sends the weather matching result to a response module when receiving confirmation information input by the user;
the response module receives the weather matching result, acquires corresponding weather handling data in the knowledge base according to the weather matching result to obtain a response and precaution control strategy, and sends the response and precaution control strategy to the threat early warning module;
and the threat early warning module also displays the response and precaution control strategy.
7. The network-based natural disaster early warning method according to claim 6, wherein the network information acquisition and processing module comprises a data mining technology unit and a data analysis and comparison unit;
the method further comprises the step of enabling the user to select the target,
the data mining technical unit mines network information and screens to obtain the first meteorological information data;
and the data analysis and comparison unit compares the first meteorological information data with the risk model to obtain the meteorological matching result.
8. The network-based natural disaster warning method as claimed in claim 7, wherein the warning system further comprises a monitoring module;
the method further comprises the step of enabling the user to select the target,
the monitoring module monitors meteorological data related to the meteorological matching result according to the meteorological matching result to obtain meteorological monitoring data, and sends the meteorological monitoring data to the network information acquisition and processing module;
and the network information acquisition processing module confirms the weather matching result according to the weather monitoring data and the risk model.
9. The network-based natural disaster early warning method according to claim 7,
the risk models comprise a conventional meteorological model and an unconventional meteorological model;
the method further comprises the step of enabling the user to select the target,
and the data analysis and comparison unit compares the first meteorological information data with the risk model, and if the first meteorological information data exceeds an early warning threshold value of a conventional meteorological model, the first meteorological information data is compared with an unconventional meteorological model to obtain a meteorological matching result.
10. The network-based natural disaster early warning method according to claim 9,
and the network information acquisition processing module acquires the second meteorological information data within second preset time and generates the risk model according to the second meteorological information data.
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| CN105741498A (en) * | 2016-04-28 | 2016-07-06 | 成都理工大学 | Method and device for monitoring and performing early warning on geological hazards |
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| CN112016772A (en) * | 2020-10-29 | 2020-12-01 | 成都中轨轨道设备有限公司 | Natural disaster early warning system and method |
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| CN117709732A (en) * | 2024-02-06 | 2024-03-15 | 北京天译科技有限公司 | Agricultural disaster report generation method and system combined with meteorological monitoring data |
| CN117709732B (en) * | 2024-02-06 | 2024-04-26 | 北京天译科技有限公司 | Agricultural disaster report generation method and system combined with meteorological monitoring data |
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