CN114547827A - Infrastructure group running state evaluation method, electronic device and storage medium - Google Patents
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Abstract
The invention provides an infrastructure group running state evaluation method, electronic equipment and a storage medium, and belongs to the technical field of running state evaluation. Firstly, dividing an urban infrastructure network based on influence factors to construct an urban infrastructure group network, wherein the influence factors comprise geological influence factors, facility construction situation influence factors and population density influence factors; secondly, constructing operation parameters of the urban infrastructure group; thirdly, acquiring a facility group running time sequence based on the city infrastructure group running parameters, normalizing the facility group running time sequence, and acquiring a facility integral running parameter time sequence for the facility group integral running parameters within a certain time; and thirdly, carrying out seepage analysis and exploring a core and a fragile facility group. The invention solves the technical problems of diversified monitoring objects, complex and changeable application scenes, insufficient utilization rate of actual monitoring equipment, no actual theoretical support of a monitoring method and incapability of supporting detailed quantitative analysis.
Description
Technical Field
The present disclosure relates to an infrastructure group operation state evaluation method, and in particular, to an infrastructure group operation state evaluation method, an electronic device, and a storage medium, and belongs to the technical field of operation state evaluation.
Background
In recent years, with the rapid development of economic society of China, the urbanization process is continuously promoted, and a plurality of important modern metropolis are planned and gradually built. However, city management faces unprecedented challenges due to the dramatic increase in city population and its derived city management problems, coupled with a series of environmental challenges arising from the deterioration of natural environments. How to solve a plurality of problems faced at present based on the current situation of city development and focus on the future development target of the city is an important problem that needs to be considered urgently by city managers. Among them, the public infrastructure on urban ground, such as roads, bridges and tunnels, transportation hubs, large buildings, public activity areas, communities and old-age institutions, is an important carrier for supporting urban development. On the basis of the established infrastructures, how to effectively monitor and master the actual operation condition of each facility, identify and investigate each hidden risk source, perform early warning on faults and accidents to be generated and make an effective processing method is an important measure for promoting the further efficient development of cities and avoiding various economic and social losses.
In response to this situation, city managers have gradually built a health monitoring system of the city infrastructure structure by collecting and processing multi-source city operation data with the aid of advanced monitoring equipment. However, due to the complexity and diversity of monitoring objects, the low utilization rate of actual monitoring equipment and the shortage of instructive theoretical support, city managers are prompted to construct a new city infrastructure operation state evaluation system.
In view of the above problems, the 'method for evaluating urban infrastructure' is 'Jinjiangqing' Fangke-Zheng-Zhong university academy (Nature science edition), 2000, (01):34-37, a method for evaluating the robustness of an infrastructure network based on a multi-layer complex network, published under No. CN201910145451.7, all propose relevant insights; however, both of the above methods have certain problems.
The problem of the method of urban infrastructure evaluation, namely Jinjiangqing, is that:
1. the method uses a correlation classification method, has a weight distribution process in an analysis process, has strong subjectivity and is easy to cause larger deviation with the actual condition;
2. there is no actual operational data of the application infrastructure and the analysis is not sufficiently effective.
The method for evaluating the robustness of the infrastructure network based on the multi-layer complex network has the following problems:
1. actual data are not applied, and the effectiveness of actual application is difficult to explain;
2. only the built multilayer network is proposed, the property of the actual infrastructure is not considered enough, and larger deviation is easily caused
3. The introduced self-consistent equation and robust analysis are insufficient for the representation of the running state of the actual infrastructure, mainly for the disturbance and the loss of the characteristic description of the infrastructure.
Disclosure of Invention
The following presents a simplified summary of the invention in order to provide a basic understanding of some aspects of the invention. It should be understood that this summary is not an exhaustive overview of the invention. It is not intended to determine the key or critical elements of the present invention, nor is it intended to limit the scope of the present invention. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is discussed later.
In view of this, the present invention provides an infrastructure group operation state evaluation method, an electronic device, and a storage medium, to solve the technical problems of diversification of monitoring objects, complex and changeable application scenarios, and insufficient utilization rate of actual monitoring devices in the prior art.
The first scheme is as follows: an infrastructure group operation state evaluation method comprises the following steps:
s1, dividing the urban infrastructure network based on the influence factors, and constructing an urban infrastructure group network;
s2, constructing operation parameters of the urban infrastructure group;
s3, acquiring a facility group running time sequence based on the city infrastructure group running parameters and normalizing;
s4, seepage analysis is carried out to discover the core and the fragile facility group.
Preferably, the influencing factors include geology, establishment conditions, and population density.
Preferably, the method for dividing the geological influence factors comprises the following steps: combining a geological settlement distribution map of a city for one year with the geographical distribution condition of a traffic district; because the urban ground subsidence in the geological subsidence distribution map can present the characteristics of flaky distribution in a partial area, under the condition that the number of traffic districts actually covered by the flaky area is not more than 3, the corresponding traffic districts are merged;
the method for dividing the facility establishment situation influence factors and the population density influence factors comprises the following steps: and dividing according to the principle that the supporting facilities and the main facilities belong to the same traffic cell.
Preferably, before the partition of the facility building situation influence factors and the population density influence factors, whether the partition of the traffic cell has the condition of infrastructure split or not is checked, if yes, the traffic cell is subdivided according to all principles of the traffic cell occupying a larger area of the corresponding infrastructure, and other irrelevant areas are not adjusted.
Preferably, the specific method for constructing the urban infrastructure group network is to allocate the key infrastructures related to urban population mobility according to a cross-region allocation mode, and the specific allocation method is as follows:
a. cascading action mode based on actual region influence divides good city infrastructure network medianAt TZ2Of (1), considering only allocation to TZ2N first-order adjacent zones TZ21, TZ22…TZ2N；
b. The requirement of D kilometers from the center point coordinate of the key infrastructure is met, the value of D needs to be referred to the specific city scale,
c. and completing the cross-region distribution of key infrastructures, and constructing a city infrastructure group network comprising L facility groups.
Preferably, the method for constructing the operation parameters of the urban infrastructure group comprises the following steps: the method comprises the following steps:
step two, summarizing all infrastructure types, and dividing the infrastructure types into static structure infrastructures and dynamic operation infrastructures;
secondly, counting static structure infrastructures and dynamic operation infrastructures in each region;
step two and step three, on the basis of the existing data, carry on the weight distribution to M kinds of facility categories, receive the weight matrix
And satisfy
；
After the weights are obtained, comparing and taking values of data in all the facility groups;
static structural infrastructure: comparing the facility numbers in all the facility groups;
taking values of high-rise buildings in the facility group i:
where max () represents the function of the maximum value,
the number of high-rise buildings in the facility group i is represented;
dynamically operating the infrastructure: comparing facility operating data within all facility groups
The geological settlement parameter value in the facility group i is as follows:
wherein the content of the first and second substances,
represents the mean value of geological settlement (gs) within the i facility group;
step two, finally obtaining the whole operation parameters of the facility group i according to the values:
preferably, the specific method for acquiring the facility group runtime sequence and normalizing is as follows: acquiring a time sequence of the integral operation parameters of the facility group within a certain time T;
the normalization method comprises the following steps: for the facility group i, all time series are sorted from large to small, and then 98% quantile data is taken
Then all time series values of the i facility group are normalized:
wherein, the first and the second end of the pipe are connected with each other,
representing the value of the operating parameter after normalization at time t,
representing the value of the operating parameter before normalization at time t.
Preferably, the specific method for performing the seepage analysis and exploring the core and the fragile facility group is as follows:
step four, setting global threshold parameters based on the whole operation parameter time sequence of the facility grouppTo distinguish two states of a facility groupF 1 : operation 1 and failure 0, the operation parameter of the urban facility group i at a certain time t is
According to the following:
dividing the infrastructure group meeting the communication state into communication subgroups, respectively recording the maximum subgroup G and the second-order subgroup SG of the number scale of the infrastructure group, and recording the proportion of the maximum subgroup G and the second-order subgroup SG to the total number L of the infrastructure group;
step two, analyzing the change conditions of the maximum size subgroup G and the second size subgroup SG at a certain time, gradually increasing the threshold value from 0 to 1 according to the graduation of 0.01pRecording the size of the maximum-scale subgroup G and the second-scale subgroup SG at all times and the facility group information in the respective subgroups, and recording the time when the second-scale subgroup SG reaches the maximum;
step four and step three, analyzing critical seepage threshold at all momentsp c The change of the size of (D) with time is summarized asp c -a t-curve;
fourthly, excavating the core and the fragile facility group of the urban facility group, wherein the specific method comprises the following steps:
step four, one, a core facility group: counting the frequency of each facility group belonging to a functional subgroup in a city within a certain time, and considering the facility group with the first C% proportion as a core facility group; thus, a facility group located within a functional sub-group is considered a core facility group; the functional subgroups refer to the largest subgroups located at a critical pre-moment;
step four, step two, fragile facility group: and comparing and analyzing the maximum change proportion of the sizes of the subgroups when the single facility group is changed into a failure state from operation, counting the whole time period T, and selecting W% of the facilities before sequencing as a fragile facility group.
The third scheme is as follows: an electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the infrastructure group operation state evaluation method according to one aspect when executing the computer program.
And the scheme is as follows: a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements an infrastructure group operation state evaluation method according to aspect one.
The invention has the following beneficial effects:
1. the city management method based on the city basic facility group introduces the concept of city basic facility group based on the key index of city operation concerned by city managers, effectively divides the city area, and makes the city management more practical according to different geographic properties, different functional attributes and heterogeneity of different operation characteristics of different areas of the city. Meanwhile, the description of the individual running state of the urban infrastructure and the correlation among different infrastructures are reasonably and effectively represented;
2. the invention considers that the monitoring and the guarantee of the whole city operation are managed according to the regional division of the infrastructure group, not only highlights the important supporting function of the city infrastructure in the city operation, but also can more effectively provide support for the decision of a city manager through analysis. The accuracy of analysis can be effectively guaranteed by the established urban infrastructure overall network through the infrastructure group nodes selected by the established 'cross-regional distribution' principle, so that the urban operation state can be more effectively evaluated from the whole situation;
3. the invention is based on the division of the city infrastructure group, counts and analyzes the actual monitoring operation data of each infrastructure group, summarizes and introduces the integral operation state parameters of the infrastructure group, and is more in line with the reality and can better evaluate the operation state of the infrastructure group compared with the failure and normal state parameters in other methods.
4. The effectiveness of the invention is supported by actual operation data, and the invention is better applied to actual city management;
5. the invention introduces seepage analysis on the basis of urban infrastructure groups, and has the support of practical theory. Meanwhile, the dynamic process of seepage analysis is matched with the operation mode of the actual urban infrastructure group, so that the urban manager can be helped to carry out detailed quantitative analysis. Furthermore, the dynamic change of the running state of the urban infrastructure group can be analyzed, the critical change moment of the state is extracted, the core and the fragile infrastructure group are excavated, the situation that the actual urban infrastructure group is subjected to deliberate attack can be effectively simulated, and a city manager can be helped to evaluate and manage urban infrastructure more effectively.
In conclusion, the method and the device can well solve a plurality of technical problems that monitoring objects are diversified, application scenes are complex and changeable, the utilization rate of actual monitoring equipment is insufficient, a monitoring method is not supported by an actual theory, and detailed quantitative analysis cannot be supported by the existing means in the prior art.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a schematic process flow diagram;
FIG. 2 is a schematic diagram showing the change of connected sub-clusters during the seepage process;
FIG. 3 is a schematic diagram showing the variation of the maximum and the second maximum clusters during the percolation process.
Detailed Description
In order to make the technical solutions and advantages of the embodiments of the present application more apparent, the following further detailed description of the exemplary embodiments of the present application with reference to the accompanying drawings makes it clear that the described embodiments are only a part of the embodiments of the present application, and are not exhaustive of all embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
In the embodiment 1, the embodiment is described with reference to fig. 1 to 3, and the method for evaluating the operation state of the infrastructure group introduces the concept of the group, combines the facility monitoring data and the geographic property, the functional attribute and the operation characteristic of each facility group, and divides the city into a plurality of facility groups, so that the method better meets the actual operation characteristics of the city infrastructure and meets the fine requirement of city management. In addition, the use attributes of the actual urban infrastructure and urban operation monitoring data are utilized, and a cross-region distribution means is combined, so that some important urban infrastructures (such as airport railway stations and the like) are subjected to cross-region multi-part detailed distribution.
The method for establishing the network for the urban infrastructure based on the cluster concept has the advantages that on one hand, the important support effect of the urban infrastructure on the actual operation of the city is based on the cluster concept, on the other hand, the introduction of the cluster concept has reasonable and effective representation on the description of the individual operation state of the urban infrastructure and the correlation among different infrastructures.
The invention introduces the analysis of seepage means on the basis of introducing the concept of the facility group, so that the network analysis of the urban infrastructure group is more reasonable. The establishment of the network (point and line) is that besides the selection of the point, whether the relevance between the points represented by the line really exists or not and whether the relevance is effectively represented in the real situation or not are all key factors for the effectiveness of the network analysis. The concept of the group is introduced, and the city infrastructure group divided by multiple factors is combined, so that the generation of lines (the association between the group and the group) is more reasonable on the basis of the selection of points. The applied percolation theory, when applied at such network level, will make the analysis more effective.
The main data used by the method is monitoring data, scheduled inspection data, facility operation parameters and other data of the urban infrastructure, the data source is clear, and the method is more reasonable and direct in application of actual seepage analysis (directly means more definite, namely analyzing the operation state parameters of the infrastructure group). Meanwhile, the provided overall operation parameters of the urban infrastructure group are more practical compared with the failure and normal state parameters in the comparison file on the basis of comprehensively planning all the data.
The seepage flow analysis introduced by the invention aims to analyze the dynamic change of the whole network when the urban infrastructure group network is subjected to some deliberate attacks, and explores the urban core and the fragile facility group at the moment of critical change. The analysis object of the invention is an urban infrastructure group (which is a reasonably established network of the infrastructure group and is not only a single infrastructure); secondly, the purpose of the analysis is to discover the network dynamics under critical conditions.
The method specifically comprises the following steps:
based on the concept of a traffic district in the traffic planning field, influence factors (geological factors), targets (supporting urban operation) and results (constructed facilities and economic development) of actual operation of urban infrastructure are analyzed, and urban infrastructure groups are further divided from three levels of geological factors, population density and facility constructed conditions. Specifically, three factors are considered: geological settlement (geological factor), the number of super high-rise buildings exceeding 200 meters (facility build situation), and the number of transportation hubs with daily passenger flow exceeding 5 ten thousand (population density).
S1, dividing the urban infrastructure network based on geology, facility building conditions and population density influence factors, and constructing an urban infrastructure group network;
the method for dividing the geological influence factors comprises the following steps: combining a geological settlement distribution map of a city for one year with the geographical distribution condition of a traffic district; because the urban ground subsidence in the geological subsidence distribution map can present the characteristics of flaky distribution in a partial area, under the condition that the number of traffic districts actually covered by the flaky area is not more than 3, the corresponding traffic districts are merged;
wherein, whether to cover depends on the proportion of the area of the traffic cell covered by the sheet-shaped area to the area of the traffic cell.
In particular, for the sheet zone Z1And a certain traffic cell TZ thereon1(corresponding areas are respectively
And
）：
wherein the content of the first and second substances,F 0 indicating whether coverage is 0, 1,
the area size of the overlapped part of the traffic zone and the sheet area is shown.
The division of the facility building situation influence factors and population density influence factors takes into consideration the supporting infrastructure of the super high-rise building and the transportation hub, for example, for a large subway line hub, the large subway line hub is often provided with other facilities, such as a transformer station, a transfer station, a subway vehicle maintenance station and the like.
The method for dividing the facility establishment situation influence factors and the population density influence factors comprises the following steps: and dividing according to the principle that the supporting facilities and the main facilities belong to the same traffic cell.
Before the division of the facility building condition influence factors and population density influence factors, whether the division of the traffic districts has the condition that the infrastructure is split or not is checked for the super high-rise buildings with the length of more than 200 meters and the traffic hubs with the daily passenger flow of more than 5 ten thousand, if yes, the traffic districts are subdivided according to all the principles of the traffic districts with larger occupied corresponding infrastructure areas, and other irrelevant areas are not adjusted.
The condition that the infrastructure is split means that more than 2 traffic cells are covered by one infrastructure at the same time.
The city integral operation monitoring and guaranteeing is managed according to the regional division of the infrastructure group, so that the important supporting function of the city infrastructure in the city operation is highlighted, and meanwhile, the analysis can more effectively provide support for the decision of a city manager. The urban infrastructure overall network constructed by the infrastructure group nodes selected according to the established 'cross-regional distribution' principle can effectively guarantee the analysis accuracy, so that the urban operation state can be evaluated more effectively from the whole situation.
And preliminarily obtaining the divided urban infrastructure network, wherein the division result is only based on the geographic position. Further, there is a need to incorporate the concept of clusters to build a network of urban infrastructure clusters. Consider a "cross-regional distribution" model, which is primarily directed to the distribution of critical infrastructure related to urban population movement. The method comprises the following steps: urban airports, urban railway stations, urban large stadiums (stadiums can accommodate more than 5 thousands of people, and other stadiums refer to stadium use attributes), important urban traffic hubs (daily passenger flow reaches a certain standard, and refers to specific city size and traffic trip scale), bridges, tunnels and important urban expressways. For these key infrastructures, the assignment is made according to the corresponding attributes, and the specific attribute assignment is referred to the key infrastructure corresponding attributes in table 1.
The specific method for constructing the urban infrastructure group network is to distribute the key infrastructures related to urban population mobility according to a cross-region distribution mode, and the specific distribution method comprises the following steps:
a. cascading action mode based on actual region influence and used for positioning in TZ in divided urban infrastructure network2Of (1), considering only allocation to TZ2N first-order adjacent zones TZ21, TZ22…TZ2N；
b. The requirement of D kilometers from the center point coordinate of the key infrastructure is met, the value of D needs to be referred to the specific city scale,
c. and completing the cross-region distribution of key infrastructures, and constructing a city infrastructure group network comprising L facility groups.
TABLE 1 corresponding Attribute assignment for Key infrastructure
Wherein, the statistical mode of the passenger flow is based on the statistical result of the passenger registered address area in a certain time period; two aspects of road network lines need to be considered, namely whether roads directly connected with key infrastructure exist in a region or not, and then the statistical result of road traffic flow distribution in a certain actual time period is taken as a standard.
Constructing an operation parameter system of the urban infrastructure group: for the existing urban infrastructure, the complex types, operation environments, maintenance conditions and the like of the existing urban infrastructure prompt the invention to provide a parameter for describing the overall operation from the perspective of urban infrastructure groups. The multi-source monitoring and statistical data need to be classified and analyzed, different weights are given to data with different levels and importance, and the data are finally summarized into a total operation parameter. The concept of city infrastructure groups is introduced, city areas are effectively divided, and city management is more practical according to the heterogeneity of different geographic properties, different functional attributes and different operation characteristics of different areas of a city;
all infrastructure classes are summarized first: all the above key infrastructures, urban road networks, high-rise buildings, sea-filling areas, hospitals, schools and endowment institutions. For these facilities, several factors need to be considered separately: the service time is over long, the rating level is low, the geological change is large, the traffic volume is extremely large, and the number of trucks is large. Secondly, the infrastructure is classified into two main categories: static structural infrastructure and dynamic operational infrastructure. The reason for this classification is to emphasize the most important features of the corresponding facilities. For facilities such as airports, railway stations and the like, the facilities are mainly infrastructure for supporting the travel of residents and the dynamic operation of cities; facilities such as high-rise buildings and old people facilities are classified into static structure infrastructures because they need to emphasize their structural changes due to the long-term construction.
S2, constructing an operation parameter system of the urban infrastructure group, wherein the method comprises the following steps:
step two, summarizing all infrastructure types, and dividing the infrastructure types into static structure infrastructures and dynamic operation infrastructures;
secondly, counting static structure infrastructures and dynamic operation infrastructures in each region; and investigating and collecting corresponding monitoring and statistical data sources, such as urban annual general survey data, urban building export lists, road, bridge and tunnel regular inspection reports, urban traffic operation management platforms and the like.
Step two and step three, on the basis of the existing data, carry on the weight distribution to M kinds of facility categories, receive the weight matrix
And satisfy
；
After the weights are obtained, comparing and taking values of data in all the facility groups;
static structural infrastructure: comparing the facility numbers in all the facility groups;
taking values of high-rise buildings in the facility group i:
where max () represents the function of the maximum value,
representing the number of high-rise buildings in the facility group i;
dynamically operating the infrastructure: comparing facility operating data within all facility groups
The geological settlement parameter value in the facility group i is as follows:
wherein the content of the first and second substances,
represents the mean value of geological settlement (gs) within the i facility group;
step two, finally obtaining the whole operation parameters of the facility group i according to the values:
s3, acquiring a facility group running time sequence based on the city infrastructure group running parameters and normalizing, wherein the specific method is as follows: acquiring a time sequence of the integral operation parameters of the facility group within a certain time T;
the normalization method comprises the following steps: for the facility group i, all time series are sorted from large to small, and then 98% quantile data is taken
Then all time series values of the i facility group are normalized:
wherein the content of the first and second substances,
representing the value of the operating parameter after normalization at time t,
representing the value of the operating parameter before normalization at time t.
S4, carrying out seepage analysis and discovering a core and a fragile facility group, wherein the specific method comprises the following steps:
step four, setting global threshold value parameters based on the whole operation parameter time sequence of the facility grouppTo distinguish two states of a facility groupF 1 : operation 1 and failure 0, the operation parameter of the urban facility group i at a certain time t is
According to the following:
dividing the infrastructure group meeting the communication state into communication subgroups, respectively recording the maximum subgroup G and the second-order subgroup SG of the number scale of the infrastructure group, and recording the proportion of the maximum subgroup G and the second-order subgroup SG to the total number L of the infrastructure group;
specifically, recording the proportion of the maximum subgroup G and the second-maximum subgroup SG in the total facility group number L, and taking three decimal places.
Step two, analyzing the change conditions of the maximum size subgroup G and the second-size subgroup SG at a certain time, gradually increasing the threshold value from 0 to 1 according to the graduation of 0.01pRecording the size of the maximum-scale subgroup G and the second-scale subgroup SG at all times and the facility group information in the respective subgroups, and recording the time when the second-scale subgroup SG reaches the maximum;
step four and step three, analyzing critical seepage threshold at all momentsp c The change of the size of (D) with time is summarized asp c -a t-curve;
fourthly, excavating the core and the fragile facility group of the urban facility group, wherein the specific method comprises the following steps:
step four, one, a core facility group: counting the frequency of each facility group belonging to a functional subgroup in a city within a certain time, and considering the facility group with the first C% proportion as a core facility group; thus, a facility group located within a functional sub-group is considered a core facility group; the functional subgroups refer to the largest subgroups located at a critical pre-moment;
step four, step two, vulnerable facility group: and comparing and analyzing the maximum change proportion of the sizes of the subgroups when the single facility group is changed into a failure state from operation, counting the whole time period T, and selecting W% of the facilities before sequencing as a fragile facility group.
The seepage analysis is introduced on the basis of the urban infrastructure group, the dynamic change of the running state of the urban infrastructure group can be analyzed, the critical change moment of the state is extracted, and the core and the fragile infrastructure group are excavated, so that the requirement of more effectively evaluating and managing the urban infrastructure is met.
The method for carrying out seepage analysis and discovering the core and fragile facility group by the fourth step is described with reference to the following steps of 2-3:
referring to FIG. 2, a global threshold parameter is set based on the obtained running parameter time series of the urban facility grouppThereby distinguishing two states of the facility groupF 1 : run (1) and fail (0), with colored facilities in fig. 1 representing run states and uncolored facilities representing fail states.
For example, the operating parameter of the urban facility group i at a certain time t is
According to the following:
referring to fig. 2, a plurality of connected sub-clusters satisfying the connected state are divided by using a breadth-first method (BFS), the sub-cluster G with the largest size (facility cluster number) and the SG with the second largest size are recorded, and the ratio of the sub-cluster G to the total facility cluster number L is recorded, specifically, three decimal places are taken. The connected sub-clusters, also called connected subgraphs, refer to that any two nodes in the sub-clusters can be connected, and the largest and the second largest connected sub-clusters are respectively the largest and the second largest sub-clusters in all the connected sub-clusters. G1 in FIG. 2 is the largest connected sub-cluster, and G2 is the second largest connected sub-cluster.
Referring to fig. 3, at a certain time, the threshold value is gradually increased from 0 to 1 according to 0.01 divisionspRecording the sizes of G and SG at all times and the facility group information in the respective sub-groups, and finally analyzing and finding out the time when the SG reaches the maximum. According to the seepage theory, the phase change of the system occurs when the second big group SG reaches the maximum. Because the system is crashed in the largest scale at the moment, the system cannot guarantee the state of global communication, and the state of overall operation is failed.
On the basis of the previous step, analyzing critical seepage threshold values at all the momentsp c Is determined byThe time change conditions are summarized intop c -t-curve. And analyzing the robustness change condition of the city running state at different times. In general terms, the amount of the solvent to be used,p c larger means that the facility cluster network is more capable of withstanding "attacks" (disabling portions of the facility cluster), i.e., more robust. The seepage analysis process is actually a process for simulating the urban facility group network to be attacked: the worse the operating condition, the facility group preferentially fails.
Finally, based on the above seepage analysis, the core and fragile facilities of the urban facility group are explored. Here, the analysis of the information on the maximum subgroups before and after the percolation critical state in the above 4b is mainly based. Before and after the seepage is critical, the sub-clusters which support the whole normal operation of the network are broken down. Therefore, the facility group located within the largest sub-group (functional sub-group) at the pre-critical time is considered as the core facility group. Counting the frequency of each facility group belonging to the functional subgroup in the city within a certain time, and considering the facility group with the top C% proportion as a core facility group. For the selection of the fragile facility group, it is taken to the extent that the influence on the clique change is the greatest. During the whole seepage process, the maximum change proportion of the size of the sub-cluster (the change condition of the whole body) is compared and analyzed when a single facility group is changed into a failure state from operation. Finally, statistics are performed over the entire time period T, and the top W% of the ranked groups are selected as vulnerable facility groups. By this, the discovery of the core and the vulnerable facility group is completed.
The technical key points of the invention are as follows:
introducing a cluster concept, and establishing a cross-regional mode city infrastructure cluster network; and based on actual multi-source data, providing running state parameters of the urban infrastructure group, and carrying out seepage analysis on the urban infrastructure group network. The introduction of seepage analysis (point seepage) into the analysis of the running state of urban infrastructure is also an innovation. And the dynamic change of the urban infrastructure group network in a critical state is analyzed, and the analysis is reasonable and rational based on the process of the previously established infrastructure group network. And the condition that the actual urban infrastructure group is subjected to deliberate attack can be effectively simulated, and suggestions for evaluating and promoting strategies are provided for discovering the core and the fragile infrastructure group.
Abbreviations and noun explanations of the present invention:
percolation Theory, The Percolation Theory, Giant Component (The Largest Component), G, maximum functional subgroup, The Second Largest functional subgroup, SG, next Largest functional subgroup, Percolation Threshold:P c the critical threshold value Traffic Zone is TZ, the Traffic cell Parameter is PRM, the Parameter Attribute is ATR, the Attribute Ground subset is gs and the Ground subsidence.
In embodiment 2, the computer device of the present invention may be a device including a processor, a memory, and the like, for example, a single chip microcomputer including a central processing unit, and the like. And the processor is used for implementing the steps of the recommendation method capable of modifying the relationship-driven recommendation data based on the CREO software when executing the computer program stored in the memory.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Embodiment 3 computer-readable storage Medium embodiments
The computer readable storage medium of the present invention may be any form of storage medium that can be read by a processor of a computer device, including but not limited to non-volatile memory, ferroelectric memory, etc., and the computer readable storage medium has stored thereon a computer program that, when the computer program stored in the memory is read and executed by the processor of the computer device, can implement the above-mentioned steps of the CREO-based software that can modify the modeling method of the relationship-driven modeling data.
The computer program comprises computer program code which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer-readable medium may contain suitable additions or subtractions depending on the requirements of legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer-readable media may not include electrical carrier signals or telecommunication signals in accordance with legislation and patent practice.
While the invention has been described with respect to a limited number of embodiments, those skilled in the art, having benefit of this description, will appreciate that other embodiments can be devised which do not depart from the scope of the invention as described herein. Furthermore, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes, and may not have been selected to delineate or circumscribe the inventive subject matter. Accordingly, many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the appended claims. The present invention has been disclosed in an illustrative rather than a restrictive sense, and the scope of the present invention is defined by the appended claims.
Claims (10)
1. An infrastructure group operation state evaluation method is characterized by comprising the following steps:
s1, dividing the urban infrastructure network based on the influence factors, and constructing an urban infrastructure group network;
s2, constructing operation parameters of the city infrastructure group;
s3, acquiring a facility group running time sequence based on the city infrastructure group running parameters and normalizing;
s4, seepage analysis is carried out to discover the core and the fragile facility group.
2. The method of claim 1, wherein the influencing factors include geology, establishment of facilities, and population density.
3. The method according to claim 2, wherein the method for dividing the influencing factors comprises: combining a geological settlement distribution map of a city for one year with the geographical distribution condition of a traffic district; because the urban ground subsidence in the geological subsidence distribution map can present the characteristics of flaky distribution in a partial area, under the condition that the number of traffic districts actually covered by the flaky area is not more than 3, the corresponding traffic districts are merged;
the method for dividing the facility establishment situation influence factors and the population density influence factors comprises the following steps: and dividing according to the principle that the supporting facilities and the main facilities belong to the same traffic cell.
4. The method as claimed in claim 3, wherein the traffic cell division is checked for infrastructure split before the division of the infrastructure establishment condition influencing factors and population density influencing factors, if yes, the traffic cell division is re-divided according to all principles of the traffic cell occupying a larger area of the corresponding infrastructure, and other irrelevant areas are not adjusted.
5. The method according to claim 4, wherein the specific method for constructing the urban infrastructure group network is to allocate key infrastructures related to urban population mobility according to a cross-region allocation mode, and the specific allocation method is as follows:
a. cascading action mode based on actual region influence and used for positioning in TZ in divided urban infrastructure network2Of (1), considering only allocation to TZ2N first-order adjacent zones TZ21, TZ22…TZ2N；
b. The requirement of D kilometers from the center point coordinate of the key infrastructure is met, the value of D needs to be referred to the specific city scale,
c. and (4) completing the trans-regional distribution of the key infrastructure, and constructing a city infrastructure group network comprising L infrastructure groups.
6. The method for evaluating an operation state of an infrastructure group according to claim 5, wherein the method for constructing the operation parameters of the city infrastructure group comprises the following steps: the method comprises the following steps:
step two, summarizing all infrastructure types, and dividing the infrastructure types into static structure infrastructures and dynamic operation infrastructures;
secondly, counting static structure infrastructures and dynamic operation infrastructures in each region;
step two and step three, on the basis of the existing data, carry on the weight distribution to M kinds of facility categories, receive the weight matrix
And satisfy
；
After the weights are obtained, comparing and taking values of data in all the facility groups;
static structural infrastructure: comparing the facility numbers in all the facility groups;
taking values of high-rise buildings in the facility group i:
where max () represents the function of the maximum value,
representing the number of high-rise buildings in the facility group i;
dynamically operating the infrastructure: comparing facility operating data within all facility groups
The geological settlement parameter value in the facility group i is as follows:
wherein the content of the first and second substances,
represents the mean value of geological settlement (gs) within the i facility group;
step two, finally obtaining the integral operation parameters of the facility group i according to the values:
7. the method for evaluating the operating condition of the infrastructure group according to claim 6, wherein the specific method for acquiring and normalizing the operating time sequence of the infrastructure group is as follows: acquiring a time sequence of the integral operation parameters of the facility group within a certain time T;
the normalization method comprises the following steps: for the facility group i, all time series are sorted from large to small, and then 98% quantile data is taken
Then all time series values of the i facility group are normalized:
wherein the content of the first and second substances,
representing the value of the operating parameter after normalization at time t,
representing the value of the operating parameter before normalization at time t.
8. The method of claim 7, wherein the specific method for analyzing seepage and exploring the core and vulnerable facility groups comprises:
step four, setting global threshold value parameters based on the whole operation parameter time sequence of the facility grouppTo distinguish two states of a facility groupF 1 : operation 1 and failure 0, the operation parameter of the urban facility group i at a certain time t is
According to the following:
dividing the infrastructure group meeting the communication state into communication subgroups, respectively recording the maximum subgroup G and the second-order subgroup SG of the number scale of the infrastructure group, and recording the proportion of the maximum subgroup G and the second-order subgroup SG to the total number L of the infrastructure group;
step two, analyzing the change conditions of the maximum size subgroup G and the second size subgroup SG at a certain time, gradually increasing the threshold value from 0 to 1 according to the graduation of 0.01pRecording the size of the maximum-scale subgroup G and the second-scale subgroup SG at all times and the facility group information in the respective subgroups, and recording the time when the second-scale subgroup SG reaches the maximum;
step four and step three, analyzing critical seepage threshold at all momentsp c The change of the size of (D) with time is summarized asp c -a t-curve;
fourthly, excavating the core and the fragile facility group of the urban facility group, wherein the specific method comprises the following steps:
step four, a core facility group: counting the frequency of each facility group belonging to a functional subgroup in a city within a certain time, and considering the facility group with the first C% proportion as a core facility group; thus, a facility group located within a functional sub-group is considered a core facility group; the functional subgroups refer to the largest subgroups located at a critical pre-moment;
step four, step two, fragile facility group: and comparing and analyzing the maximum change proportion of the sizes of the subgroups when the single facility group is changed into a failure state from operation, counting the whole time period T, and selecting W% of the facilities before sequencing as a fragile facility group.
9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method for evaluating an operation state of an infrastructure group according to any one of claims 1 to 8 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, wherein the computer program, when executed by a processor, implements an infrastructure group operational status evaluation method as claimed in any one of claims 1 to 8.
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