CN109740898B - Road network reliability assessment method, system, terminal and medium - Google Patents
Road network reliability assessment method, system, terminal and medium Download PDFInfo
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Abstract
The invention discloses a road network reliability evaluation method, which comprises the steps of obtaining geographic space position data, road data and historical geological disaster data of a road section of an area to be evaluated; constructing a road complex network model according to the obtained geospatial position data and road data; constructing disaster situation interference modes of different types according to historical geological disaster data; simulating different types of disaster situation interference modes to attack a road complex network model; and analyzing and calculating the network overall connectivity and the network high-efficiency connectivity of the road complex network model in an initial state and a simulated attack state, and evaluating the reliability of the road section of the area to be evaluated by combining the importance of the road section, the relative reduction rate of the maximum connected subgraph scale and the relative reduction rate of the whole network connection efficiency. The method greatly improves the spatial precision of the risk assessment result, can find out real high-risk areas, and provides reliable basis for road engineering prevention and control planning.
Description
Technical Field
The invention relates to the technical field of road network reliability evaluation, in particular to a road network reliability evaluation method, a road network reliability evaluation system, a road network reliability evaluation terminal and a road network reliability evaluation medium.
Background
The mountain area of china is vast, accounting for about 69% of the total land area, while about 16% of the population is distributed in the southwest mountain area. In general, mountain areas are fragile in habitat, construction land is compact, infrastructure construction levels such as roads are relatively low, and road network vulnerability is high; meanwhile, the road system is influenced by factors such as special topography, stratum lithology, geological structure and the like, ground disasters are easy to occur, the functions of partial road sections of the road system in the mountain area are invalid, and the reliability of the road network is greatly influenced. In the year 2008, the earthquake is 8.0 grade in the Wenchuan area, and the regional road network system is seriously damaged, so that the earthquake relief work and the post-disaster reconstruction work are seriously hindered. The current research content of the reliability of the road traffic network is focused on the knowledge of the overall characteristics and static structural rules of the road traffic network, or the general generalization of the robustness and vulnerability performance of the network in a random or combined simple interference mode, the association with the actual disaster scene is less in corresponding analysis, and the road construction is fully affected by natural disasters such as debris flow, collapse, boulder and the like for many years, so that the development of urban and rural construction is limited, and the problem of how to reduce the influence of sudden disasters on the reliability service capability of the road network is an urgent real problem to be solved.
Disclosure of Invention
Aiming at the defects in the prior art, the embodiment of the invention provides a road network reliability evaluation method, a system, a terminal and a medium, which are used for attacking a road complex network model by simulating different disaster situation interference modes, analyzing and judging the road section reliability of an area to be evaluated and providing a reliable basis for road engineering prevention and control planning.
In a first aspect, a road network reliability evaluation method provided by an embodiment of the present invention includes:
obtaining geographical space position data of a road section of an area to be evaluated, road data and historical geological disaster data of the area to be evaluated;
constructing a road complex network model according to the obtained geographic space position data and the road data of the road section;
adopting computer simulation to construct different types of disaster situation interference modes according to the historical geological disaster data;
attacking road complex network models by different types of disaster situation interference modes;
analyzing and calculating the network overall connectivity and the network high-efficiency connectivity of the road complex network model in an initial state and a simulated attack state, and calculating the maximum connected subgraph scale and the full network connection efficiency in the initial state; and carrying out reliability evaluation on the road section of the area to be evaluated by combining the importance of the road section, the relative descending rate of the maximum connected sub-graph scale and the relative descending rate of the full-network communication efficiency, and the relative descending rate of the full-network communication efficiency to obtain the evaluation result of the road section of the area to be evaluated.
In a second aspect, the road network reliability evaluation system provided by the embodiment of the invention comprises a data acquisition module, a road complex network model building module, a disaster situation interference simulation module, a simulation attack module and a data processing module;
the data acquisition module is used for acquiring geographic space position data of a road section of the region to be evaluated, road data and historical geological disaster data of the region to be evaluated;
the road complex network model building module is used for building a road complex network model according to the obtained geographic space position data of the road section and the road data;
the disaster situation interference simulation module is used for constructing different types of disaster situation interference modes by adopting computer simulation according to historical geological disaster data;
the simulation attack module is used for simulating the road complex network model to be attacked by different disaster situation interference modes;
the data processing module is used for analyzing and calculating the network overall connectivity and the network high-efficiency connectivity of the road complex network model in the initial state and the simulated attack state, and calculating the maximum connected sub-graph scale and the full-network connection efficiency in the initial state; and carrying out reliability evaluation on the road section of the area to be evaluated by combining the importance of the road section, the relative descending rate of the maximum connected sub-graph scale and the relative descending rate of the full-network communication efficiency, and the relative descending rate of the full-network communication efficiency to obtain the evaluation result of the road section of the area to be evaluated.
In a third aspect, an embodiment of the present invention further provides an intelligent terminal for evaluating reliability of a road network, including a processor, an input device, an output device, and a memory, where the processor, the input device, the output device, and the memory are connected to each other, and the memory is configured to store a computer program, where the computer program includes program instructions, and where the processor is configured to invoke the program instructions to perform the method described in the foregoing embodiment.
In a fourth aspect, embodiments of the present invention also provide a computer-readable storage medium storing a computer program comprising program instructions which, when executed by a processor, cause the processor to perform the method described in the above embodiments.
The invention has the beneficial effects that:
according to the road network reliability assessment method, system, terminal and medium provided by the embodiment of the invention, through simulating the road network model of the area to be assessed of the interference of various disaster situations, the risk analysis is realized from the angle of 'future scenes', the reliability of the road section of the area to be assessed is analyzed and judged, the spatial precision of the risk assessment result is greatly improved, the real high risk area can be found, and the reliable basis is provided for the road engineering prevention and treatment planning. The method is particularly suitable for reliability evaluation of the multi-disaster road network, provides reliable basis for road engineering prevention and control planning, and improves the reliability service capability of the multi-disaster area road network.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. Like elements or portions are generally identified by like reference numerals throughout the several figures. In the drawings, elements or portions thereof are not necessarily drawn to scale.
Fig. 1 is a flowchart showing a road network reliability evaluation method according to a first embodiment of the present invention;
fig. 2 shows a road network state diagram of a large-river basin constancy section in the first embodiment of the present invention;
FIG. 3 is a schematic diagram showing the construction of a current road complex network model in a first embodiment of the present invention;
fig. 4 is a schematic diagram showing the overall connectivity change of a road network in a sporadic disaster interference scenario in a first embodiment of the present invention;
fig. 5 shows a schematic diagram of efficient connectivity change of a road network in a sporadic disaster interference scenario in a first embodiment of the present invention;
fig. 6 is a schematic diagram showing the overall connectivity change of a road network in a regional disaster interference scenario mode according to a first embodiment of the present invention;
fig. 7 is a schematic diagram showing efficient connectivity change of a road network in a regional disaster interference scenario mode according to a first embodiment of the present invention;
FIG. 8 shows a diagram of a road network structure after a post-earthquake of a Twain super-huge earthquake in the year 2008, 5 months and 12 days in the first embodiment of the invention;
FIG. 9 is a view showing a construction of a road network after a seismic post-earthquake in a first embodiment of the invention in the form of a 2013 "4.20" reed mountain;
FIG. 10 is a diagram showing a road network construction diagram after earthquake of grade 6.3 in the city of Kangding, 11.22.2014, in a first embodiment of the present invention;
fig. 11 is a schematic structural view showing a first embodiment of a road network reliability evaluation system according to the present invention;
fig. 12 is a schematic structural diagram of a first embodiment of an intelligent terminal for evaluating the reliability of a road network according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. 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.
It should be understood that the terms "comprises" and "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
As used in this specification and the appended claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]".
It is noted that unless otherwise indicated, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.
Fig. 1 shows a flowchart of a road network reliability evaluation method according to a first embodiment of the present invention, the method includes:
and S1, obtaining geographical space position data, road data and historical geological disaster data of a road section of the region to be evaluated.
The geographical space position data of the road section of the area to be evaluated, the road data and the historical address disaster data of the area to be evaluated are derived from on-site investigation and investigation data, and a traffic network in the latest period is built by combining GIS data processing, *** Earth software, statistics annual service and other tools.
S2, constructing a road complex network model according to the obtained geospatial position data and the road data of the road section.
And according to the obtained geospatial position data and road data of the road section, determining a semantic model, and then constructing a road complex network model on the Pajek network platform.
And S3, constructing different types of disaster situation interference modes by adopting computer simulation according to the historical geological disaster data.
And constructing a disaster situation interference mode by utilizing computer simulation according to the historical geological disaster data. The disaster situation interference patterns comprise sporadic geological disaster interference patterns, regional geological disaster interference patterns and strong earthquake geological disaster interference patterns. Sporadic geological disaster interference, namely, disaster interference such as collapse, landslide, subgrade collapse and the like of a certain road section caused by rock and soil loosening at a certain place caused by heavy rain or ergonomic activities; regional geological disaster interference, namely larger-scale rock and soil loosening at a certain place caused by heavy rain, human engineering activities or small earthquakes, causes the disaster interference of collapse, debris flow and the like on a plurality of road sections within a certain range; the strong earthquake geological disaster interference, namely the strong earthquake generated by geological structure activities causes large-scale rock and soil loosening, and causes large-scale interference to regional road networks, which is generally called as strong earthquake of more than 6 grades.
S4, simulating and attacking the complex road network model by using different disaster situation interference modes.
In a real scene, when a road encounters failure of an interference function, a network part is possibly separated from a main body structure to form an independent part, so that the road complex network model is simulated and attacked by different disaster situation interference modes, and the overall connectivity of the road network and the efficient connectivity of the road network can be judged. The road network overall connectivity and the road network high-efficiency connectivity are used as road network reliability analysis measure indexes, and the technical indexes corresponding to the road network overall connectivity and the road network high-efficiency connectivity are respectively the maximum connected subgraph scale and the full network connected efficiency.
S5, analyzing and calculating the overall connectivity and the high-efficiency connectivity of the network of the road complex network model in the initial state and the simulated attack state, and calculating the maximum connected subgraph scale and the full-network connection efficiency in the initial state; and carrying out reliability evaluation on the road section of the area to be evaluated by combining the importance of the road section, the relative descending rate of the maximum connected sub-graph scale and the relative descending rate of the full-network communication efficiency, and the relative descending rate of the full-network communication efficiency to obtain the evaluation result of the road section of the area to be evaluated.
The maximum connected subgraph refers to a sub-network that connects all nodes in the complex network model with the least edges. The maximum connected subgraph size refers to the ratio of the number of nodes in the maximum connected subgraph to the number of all nodes in the complex network model. The maximum connected subgraph scale is used for analyzing the capacity of the node to influence the overall connectivity of the network, and the calculation formula of the maximum connected subgraph scale S is as follows: s=n'/N, where S represents the size of the maximum connected sub-graph scale; n represents the number of nodes of the road complex network model when not attacked; and N' represents the node number of the maximum connected subgraph after the complex road network model is attacked. In a real scenario, when a road encounters failure of an interference function, a network may be caused to be partially separated from a main structure to form an independent part. In the complex network analysis method, the network overall connectivity refers to the capability that the residual structure can still be kept as a connected whole when the network is in an interference damaged state, and the larger the maximum connected sub-graph scale is, the better the overall connectivity of the road complex network is indicated. Let Δn=n-N', where Δn is the variation of the maximum connected subgraph scale, and N represents the number of nodes of the road complex network model when not attacked; and N' represents the node number of the maximum connected subgraph after the complex road network model is attacked. The relative decline rate of the size of the maximum connected subgraph scale is represented by s, and the calculation formula of s is as follows:
wherein s is the relative descending rate of the size of the maximum connected subgraph, and N' represents the node number of the maximum connected subgraph after the complex road network model is attacked; n represents the number of nodes of the complex network model of the road when not attacked.
The whole network communication efficiency of the road complex network model is that the size of the change of the road network performance caused by the failure of a certain station or line is determined through the change of the value of the whole network communication efficiency.
The specific method for calculating the communication efficiency of the whole network comprises the following steps: the adopted calculation formula is as follows:
wherein E represents the communication efficiency of the whole network; n represents the number of nodes in the complex network model of the road; i represents an ith node in the complex network model of the road; j represents a j-th node in the complex road network model; epsilon ij Representing the efficiency between a node i and a node j in a complex road network model; d, d ij Representing the distance between a model node i and a node j in a complex road network; n, i and j are integers. Let Δe=e-E ', where Δe is the amount of change in the full-network communication efficiency, E is the full-network communication efficiency before the node fails, E' is the full-network communication efficiency after the node fails, E represents the relative drop rate of the full-network communication efficiency, and the calculation formula of E is: />
According to the road network reliability assessment method provided by the embodiment of the invention, through the road network model simulating the areas to be assessed of the interference of various disaster situations, the risk analysis is realized from the angle of future situations, the road section reliability of the areas to be assessed is analyzed and judged, the space precision of the risk assessment result is greatly improved, the real high-risk areas can be found, and the reliable basis is provided for the road engineering prevention and treatment planning. The method is particularly suitable for reliability evaluation of the multi-disaster road network, provides reliable basis for road engineering prevention and control planning, and improves the reliability service capability of the multi-disaster area road network.
The following describes in detail the above examples using the selection of the large river basin constancy section area as the research target.
The transition zone from the Sichuan plateau to the basin in the conding section area of the large river basin has extremely complex geological and geographic environment, and road construction is greatly influenced by terrain factors, so that the method has strong representativeness. The area is in a disaster-prone area, the ecological environment is fragile, and road construction is affected by natural disasters such as debris flow, collapse, boulders and the like for many years, so that the development of local urban and rural construction is limited. As shown in fig. 2, a road network state diagram of a large-ferry river basin constancy section is shown. The road network state diagram is subjected to semantic conversion, the roads between adjacent intersections or village points are subjected to node numbering (namely, the edges of the roads are used as numbers, the edges of the roads in the complex network are used as network nodes thereof), the intersections between the roads are used as edges, a current road complex network model is built on a Pajek software platform, the current road complex network model is provided with 251 nodes and 360 edges in total, and the built current road complex network model schematic diagram is shown in fig. 3. And respectively calculating the initial maximum connected subgraph scale of the road network to be 251 according to the calculation formulas of the maximum connected subgraph scale and the full-network connection efficiency, wherein the initial network connection efficiency is 9.93%.
And adopting computer simulation to construct different types of disaster situation interference modes according to the historical geological disaster data, and adopting different interference strategies under the different types of disaster situation interference modes. The adopted interference strategy is an occasional disaster interference scenario, the corresponding interference strategy is random attack, one node in the road network model is randomly selected each time to attack, then each index of the current road network is recalculated, and after recovery, the nodes in the road network model are selected to attack until all the nodes are attacked; the regional geological disaster interference scene corresponds to an interference strategy, wherein the interference strategy is selected for attack, nodes in a certain disaster point influence range in the road network model are selected for attack each time, then each index of the current road network model is recalculated, and nodes in the certain disaster point influence range in the road network model are selected for attack after recovery until the nodes in all disaster point influence ranges are attacked; the strong earthquake geological disaster interference scenario corresponds to the interference strategy, the important geological disasters occurring in history are simulated, the nodes which fail in the ground disaster event in the history data are selected to attack, and a plurality of nodes in different positions are attacked at one time, namely, the large-range road sections in different geographical positions are simultaneously interfered. To simplify the model, the following assumptions are made for the above-described interference strategy: nodes in the road network model have no protective measures, and the nodes can be disabled by one attack; only the topology structure of the road network model is researched, and after a node is attacked, the node and all edges connected with the node are deleted.
The road network model is subjected to random attack by adopting the sporadic disaster interference scenario mode, random attack is carried out on each road side, the maximum connected subgraph scale and the full network communication efficiency of the road network in the sporadic disaster interference scenario mode are obtained through calculation, the diagram is shown in fig. 4, the overall connectivity change schematic diagram of the road network in the sporadic disaster interference scenario mode is shown, and the diagram is shown in fig. 5, the efficient connectivity change schematic diagram of the road network in the sporadic disaster interference scenario mode is shown. As can be seen from fig. 4 and 5, when different roads are damaged, the overall connectivity and the efficient connectivity of the network change to different extents, and the distribution of disaster points with the drop rate of more than 10% after the overall connectivity and the efficient connectivity are 9.96%, 10.76% and more than 20% of the total number respectively are 5.97% and 5.98%. If the road segment of the number 31 (S211 to the road section of the great fire village Jin Tong) is damaged, the overall connectivity of the road network is reduced by cliff, the reduction rate is 39.04%, the overall road network becomes two independent groups, the high-efficiency connectivity of the road network is rapidly reduced, the reduction rate is 28.57%, namely, after the road segment is in failure, the number of the road segments which keep the connected state is only about 60% of the original proportion, the road network is obviously split into two independent groups, meanwhile, the paths which need to be experienced by the connection between a plurality of road nodes are prolonged, and similar change rules are also presented after other road damage. Meanwhile, after the road with the number 46 (two estuaries village to the small Jin Xianjin tung road section) is damaged, the overall connectivity and the high-efficiency connectivity of the road network are reduced by less than 1 percent, and almost no change exists. Therefore, for the road network in southwest, the influence of the failure of certain road sections on the whole network structure is large, the reliability is greatly changed, and the road network needs to be screened.
The road network model is subjected to simulation selection attack by adopting the regional disaster interference contextual model, each road side is subjected to selection attack, the maximum connected subgraph scale and the full network communication efficiency of the road network in the regional disaster interference contextual model are obtained through calculation, the diagram is shown in fig. 6, the overall connectivity change schematic diagram of the road network in the regional disaster interference contextual model is shown, and the diagram is shown in fig. 7, the efficient connectivity change schematic diagram of the road network in the regional disaster interference contextual model is shown. As can be seen from fig. 6 and 7, the interference of different geological disaster points has different influence degrees on the reliability of the road network, such as "the rural road section of the great fire land and the Jin Tong road section where the" mountain dangerous rock behind the three-in-one village, the house ditch village "has influence, the maximum communication sub-graph scale reduction rate is 37.45%, and the whole network communication efficiency reduction rates are 29.82%; in the disaster area of the 'Sanhe village landslide', after the road network is interfered, the overall connectivity of the road network system is reduced by 0.40 percent, the connectivity is reduced by 0.66 percent, and almost no change exists. In a real disaster scenario, the geological disaster points are high in risk, road sections in the affected range are critical, people life and property safety in the area are seriously affected if damaged, important prevention and treatment are needed for the geological disaster points, and engineering treatment or reinforcement is needed for the road sections in the affected range.
The strong earthquake geological disaster interference mode is mainly characterized in that historical disaster information is analyzed, processed and converted into experience and useful knowledge simulation to generate representative strong earthquake geological disaster scenes, and the maximum connected subgraph scale and the full-network communication efficiency of the road network in the regional disaster interference scene mode are obtained through calculation. Historical disaster description: the Wenchuan extra-large earthquake is 5 months and 12 days in 2008, the eastern region of Kangding city has strong shock feeling, and multiple collapse is caused; in 2013, the earthquake local area of the reed mountain has strong earthquake sense, and part of the original 144 geological disaster points in the convalescence city are deformed and aggravated, and part of the original 144 geological disaster points are disaster-caused, and a new autonomous disaster point 14 is initiated; on the 11 th and 22 th 2014, 6.3-level earthquakes occur near the public country of Kangding city tower, 5 people die due to earthquake accumulation, and more than 80 people are injured. As shown in table 1, the overall connectivity and the change condition of the high-efficiency connectivity characteristic value of the road network under the condition of strong earthquake geological disaster interference are shown.
TABLE 1 Whole connectivity and efficient connectivity characteristic value variation table of road network under strong earthquake geological disaster interference scenario
As shown in fig. 8, a road network structure diagram after a venturi major earthquake at 5 months 12 days 2008 is shown, and as shown in fig. 9, a road network structure diagram after a reed mountain earthquake at 2013 "4.20" is shown; as shown in fig. 10, a road network structure diagram after earthquake at 6.3 level in the city of conding tower, 11.22.2014 is shown. As can be seen from fig. 8-10, the road network structure is extremely unstable in large-scale attack state, the minimum reduction of the maximum connected subgraph scale is 101, the reduction rate is 59.76%, the minimum reduction of the whole network communication efficiency is 0.0412, the reduction rate is 58.44%, and the influence degree is far higher than that of sporadic and regional disaster interference scene modes.
The road sections are classified into three grades of high-risk, medium-risk and low-risk according to importance in the interference analysis of the above 3 disaster situations, and the evaluation principle is as follows: the method comprises the steps that after the road section or the road section within the influence range of the geological disaster is interfered, the high-efficiency connectivity of the whole network or the overall connectivity reduction rate X is more than or equal to 20%, and then the road section within the influence range of the geological disaster is evaluated as a high-risk road section; if the high-efficiency connectivity or the overall connectivity drop rate of the whole network after being interfered is more than or equal to 20 percent and more than or equal to 5 percent, the road sections in the influence range of the road sections and the geological disaster point are evaluated as medium-risk road sections, the rest road sections are evaluated as low-risk road sections, and a road grading planning database based on the liability and the risk grading is established according to the existing ground disaster data.
In the first embodiment described above, a road network reliability evaluation method is provided, and correspondingly, the present application also provides a road network reliability evaluation system. Since the apparatus embodiments are substantially similar to the method embodiments, the description is relatively simple, and reference is made to the description of the method embodiments for relevant points. The device embodiments described below are merely illustrative.
As shown in fig. 11, the present invention further provides a schematic structural diagram of a first embodiment of a road network reliability evaluation system, where the system includes a data acquisition module, a road complex network model building module, a disaster scenario interference simulation module, a simulation attack module, and a data processing module;
the data acquisition module is used for acquiring geographic space position data of a road section of the region to be evaluated, road data and historical geological disaster data of the region to be evaluated;
the road complex network model building module is used for building a road complex network model according to the obtained geographic space position data and the road data of the road section;
the disaster situation interference simulation module is used for simulating and constructing different types of disaster situation interference modes by adopting a computer according to the historical geological disaster data;
the simulation attack module is used for simulating the road complex network model to be attacked by different disaster situation interference modes;
the data processing module is used for analyzing and calculating the network overall connectivity and the network high-efficiency connectivity of the road complex network model in the initial state and the simulated attack state, and calculating the maximum connected subgraph scale and the full network connection efficiency in the initial state; and carrying out reliability evaluation on the road section of the area to be evaluated by combining the importance of the road section, the relative descending rate of the maximum connected sub-graph scale and the relative descending rate of the full-network communication efficiency, and the relative descending rate of the full-network communication efficiency to obtain the evaluation result of the road section of the area to be evaluated.
The maximum connected subgraph refers to a sub-network that connects all nodes in the complex network model with the least edges. The maximum connected subgraph size refers to the ratio of the number of nodes in the maximum connected subgraph to the number of all nodes in the complex network model. The maximum connected subgraph scale is used for analyzing the capacity of the node to influence the overall connectivity of the network, and the calculation formula of the maximum connected subgraph scale S is as follows: s=n'/N, where S represents the size of the maximum connected sub-graph scale; n represents the number of nodes of the road complex network model when not attacked; n' represents the maximum communication of the complex network model of the road after being attackedNumber of nodes in the subgraph. In a real scenario, when a road encounters failure of an interference function, a network may be caused to be partially separated from a main structure to form an independent part. In the complex network analysis method, the network overall connectivity refers to the capability that the residual structure can still be kept as a connected whole when the network is in an interference damaged state, and the larger the maximum connected sub-graph scale is, the better the overall connectivity of the road complex network is indicated. Let Δn=n-N', where Δn is the variation of the maximum connected subgraph scale, and N represents the number of nodes of the road complex network model when not attacked; and N' represents the node number of the maximum connected subgraph after the complex road network model is attacked. The relative decline rate of the size of the maximum connected subgraph scale is represented by s, and the calculation formula of s is as follows:
wherein s is the relative descending rate of the size of the maximum connected subgraph, and N' represents the node number of the maximum connected subgraph after the complex road network model is attacked; n represents the number of nodes of the complex network model of the road when not attacked.
The whole network communication efficiency of the road complex network model is that the size of the change of the road network performance caused by the failure of a certain station or line is determined through the change of the value of the whole network communication efficiency.
The specific method for calculating the communication efficiency of the whole network comprises the following steps: the adopted calculation formula is as follows:
wherein E represents the communication efficiency of the whole network; n represents the number of nodes in the complex network model of the road; i represents an ith node in the complex network model of the road; j represents a j-th node in the complex road network model; epsilon ij Representing the efficiency between a node i and a node j in a complex road network model; d, d ij Representing the distance between a model node i and a node j in a complex road network; n, i and j are integers. Let Δe=e-E ', where Δe is the amount of change in the overall network communication efficiency, E is the overall network communication efficiency before the node failure, E' is the overall network communication efficiency after the node failure, and E represents the relative rate of decline in the overall network communication efficiency, EThe calculation formula is as follows: />
According to the road network reliability evaluation system provided by the embodiment of the invention, through simulating the road network model of the region to be evaluated, which is interfered by various disaster situations, the risk analysis is realized from the angle of future scenes, the reliability of the road section of the region to be evaluated is analyzed and judged, the space precision of the risk evaluation result is greatly improved, the real high-risk region can be found, and the reliable basis is provided for the road engineering prevention and treatment planning. The method is particularly suitable for reliability evaluation of the multi-disaster road network, provides reliable basis for road engineering prevention and control planning, and improves the reliability service capability of the multi-disaster area road network.
The present invention also provides a first embodiment of an intelligent terminal for evaluating the reliability of a road network, as shown in fig. 12, which shows a schematic structural diagram of the intelligent terminal, the terminal comprising a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory being interconnected, the memory being for storing a computer program comprising program instructions, the processor being configured for invoking the program instructions for performing the method described in the above embodiments.
It should be appreciated that in embodiments of the present invention, the processor may be a central processing unit (Central Processing Unit, CPU), which may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSPs), application specific integrated circuits (Application Specific Integrated Circuit, ASICs), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The input devices may include a touch pad, a fingerprint sensor (for collecting fingerprint information of a user and direction information of a fingerprint), a microphone, etc., and the output devices may include a display (LCD, etc.), a speaker, etc.
The memory may include read only memory and random access memory and provide instructions and data to the processor. A portion of the memory may also include non-volatile random access memory. For example, the memory may also store information of the device type.
In a specific implementation, the processor, the input device, and the output device described in the embodiments of the present invention may execute the implementation described in the method embodiment provided in the embodiments of the present invention, or may execute the implementation of the system embodiment described in the embodiments of the present invention, which is not described herein again.
In a further embodiment of the invention, a computer-readable storage medium is provided, which stores a computer program comprising program instructions that, when executed by a processor, cause the processor to perform the method described in the above embodiment.
The computer readable storage medium may be an internal storage unit of the terminal according to the foregoing embodiment, for example, a hard disk or a memory of the terminal. The computer readable storage medium may also be an external storage device of the terminal, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the terminal. Further, the computer-readable storage medium may also include both an internal storage unit and an external storage device of the terminal. The computer-readable storage medium is used to store the computer program and other programs and data required by the terminal. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working procedures of the terminal and the unit described above may refer to the corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In several embodiments provided in the present application, it should be understood that the disclosed terminal and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. In addition, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices, or elements, or may be an electrical, mechanical, or other form of connection.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the 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 scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention, and are intended to be included within the scope of the appended claims and description.
Claims (6)
1. A road network reliability evaluation method, characterized by comprising:
obtaining geographical space position data of a road section of an area to be evaluated, road data and historical geological disaster data of the area to be evaluated;
constructing a road complex network model according to the obtained geographic space position data and the road data of the road section;
adopting computer simulation to construct different types of disaster situation interference modes according to the historical geological disaster data;
simulating different types of disaster situation interference modes to attack a road complex network model;
analyzing and calculating the network overall connectivity and the network high-efficiency connectivity of the road complex network model in an initial state and a simulated attack state, and calculating the maximum connected subgraph scale and the full network connection efficiency in the initial state; the method comprises the steps that under different types of disaster situation interference modes, reliability evaluation is carried out on a road section of a region to be evaluated by combining the importance of the road section, the relative decline rate of the maximum communication sub-graph scale and the relative decline rate of the full-network communication efficiency, the relative decline rate of the full-network communication efficiency and the maximum communication sub-graph scale of a road complex network model, so as to obtain an evaluation result of the road section of the region to be evaluated;
the specific method for calculating the maximum connected subgraph scale comprises the following steps:
the adopted calculation formula is as follows: s=n'/N, where S represents the size of the maximum connected sub-graph scale; n' represents the number of nodes of the maximum connected subgraph after the road complex network model is attacked; n represents the number of nodes of the road complex network model when not attacked;
the specific method for calculating the relative reduction rate of the maximum connected subgraph scale comprises the following steps:
let Δn=n-N', denote the relative rate of decrease in the magnitude of the maximum connected subgraph scale with s, and the s calculation formula is:
the specific method for calculating the whole network communication efficiency comprises the following steps:
the adopted calculation formula is as follows:
wherein E represents the communication efficiency of the whole network; n represents the number of nodes in the complex network model of the road; i represents an ith node in the complex network model of the road; j represents a j-th node in the complex road network model; epsilon ij Representing the efficiency between a node i and a node j in a complex road network model; d, d ij Representing the distance between a model node i and a node j in a complex road network; n, i and j are integers;
the specific method for calculating the relative drop rate of the whole network communication efficiency comprises the following steps:
let Δe=e-E ', represent the relative drop rate of the full network communication efficiency with E, E' is the full network communication efficiency after the node failure, and the calculation formula of E is:
2. the road network reliability assessment method according to claim 1, wherein the disaster scenario interference patterns include sporadic geological disaster interference patterns, regional geological disaster interference patterns and strong earthquake geological disaster interference patterns.
3. The road network reliability evaluation system is characterized by comprising a data acquisition module, a road complex network model building module, a disaster situation interference simulation module, a simulation attack module and a data processing module;
the data acquisition module is used for acquiring geographic space position data of a road section of the region to be evaluated, road data and historical geological disaster data of the region to be evaluated;
the road complex network model building module is used for building a road complex network model according to the obtained geographic space position data of the road section and the road data;
the disaster situation interference simulation module is used for constructing different types of disaster situation interference modes by adopting computer simulation according to historical geological disaster data;
the simulation attack module is used for simulating the road complex network model to be attacked by different disaster situation interference modes;
the data processing module is used for analyzing and calculating the network overall connectivity and the network high-efficiency connectivity of the road complex network model in the initial state and the simulated attack state, and calculating the maximum connected sub-graph scale and the full-network connection efficiency in the initial state; the method comprises the steps that under different types of disaster situation interference modes, reliability evaluation is carried out on a road section of a region to be evaluated by combining the importance of the road section, the relative decline rate of the maximum communication sub-graph scale and the relative decline rate of the full-network communication efficiency, the relative decline rate of the full-network communication efficiency and the maximum communication sub-graph scale of a road complex network model, so as to obtain an evaluation result of the road section of the region to be evaluated;
the specific method for calculating the maximum connected subgraph scale comprises the following steps:
the adopted calculation formula is as follows: s=n'/N, where S represents the size of the maximum connected sub-graph scale; n' represents the number of nodes of the maximum connected subgraph after the road complex network model is attacked; n represents the number of nodes of the road complex network model when not attacked;
the specific method for calculating the relative reduction rate of the maximum connected subgraph scale comprises the following steps:
let Δn=n-N', denote the relative rate of decrease in the magnitude of the maximum connected subgraph scale with s, and the s calculation formula is:
the specific method for calculating the whole network communication efficiency comprises the following steps:
the adopted calculation formula is as follows:
wherein E represents the communication efficiency of the whole network; n represents the number of nodes in the complex network model of the road; i represents an ith node in the complex network model of the road; j represents a j-th node in the complex road network model; epsilon ij Representing the efficiency between a node i and a node j in a complex road network model; d, d ij Representing the distance between a model node i and a node j in a complex road network; n, i and j are integers;
the specific method for calculating the relative drop rate of the whole network communication efficiency comprises the following steps:
let Δe=e-E ', represent the relative drop rate of the full network communication efficiency with E, E' is the full network communication efficiency after the node failure, and the calculation formula of E is:
4. the road network reliability assessment system of claim 3, wherein the disaster scenario interference profile comprises an sporadic geological disaster interference profile, a regional geological disaster interference profile, and a strong earthquake geological disaster interference profile.
5. An intelligent terminal for assessing the reliability of a road network, comprising a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory being interconnected, the memory being for storing a computer program, the computer program comprising program instructions, characterized in that the processor is configured to invoke the program instructions to perform the method of any of claims 1-2.
6. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program comprising program instructions which, when executed by a processor, cause the processor to perform the method of any of claims 1-2.
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