Drainage pipeline node importance degree evaluation method, device, equipment and medium

Abstract

The embodiment of the invention provides a drainage pipeline node importance degree evaluation method and device, equipment and a medium. The method comprises the following steps: constructing an adjacent matrix and a simulation model corresponding to the drainage pipe network, wherein the adjacent matrix is used for indicating a topological relation between a plurality of drainage nodes and drainage pipelines in the drainage pipe network; determining a plurality of nodes to be optimized from the drainage nodes based on the adjacent matrix; performing optimization processing on the plurality of to-be-optimized nodes, and adopting the simulation model to obtain an importance parameter of each to-be-optimized node; and according to the importance parameters corresponding to the plurality of to-be-optimized nodes, performing importance evaluation on the plurality of to-be-optimized nodes. The method is used for evaluating the importance degree of the drainage nodes, optimization of the drainage pipeline simulation model is achieved, simulation time consumption is reduced, and the practicability and timeliness of the simulation model are improved.

Description

Technical Field

[0001] The present application relates to the technical field of drainage pipes, and in particular to a method, device, equipment and medium for evaluating the importance of drainage pipe nodes. Background Art

[0002] The urban drainage network system is an important urban infrastructure and a key project for urban pollution prevention and control and urban drainage and waterlogging prevention. An urban drainage system simulation model is established to simulate the urban drainage process and the water flow conditions in each part of the drainage pipe in order to manage and control the drainage network system.

[0003] At present, based on the urban drainage system simulation model, it is possible to simulate the urban drainage process under different design or operating conditions, and guide the optimization design of the drainage system or the formulation of operation plans.

[0004] However, due to the large number of drainage nodes and pipes in the urban drainage system and the complex topological structure, the calculation of the urban drainage system model is extremely time-consuming, so that design optimization is difficult to achieve due to the long time consumption; the operation plan cannot meet the timeliness requirements of real-time operation. Summary of the invention

[0005] The embodiments of the present application provide a drainage pipe node importance assessment method, device, equipment and medium for assessing the importance of drainage nodes, optimizing the drainage pipe simulation model, reducing simulation time, and improving the practicality and timeliness of the simulation model.

[0006] In a first aspect, an embodiment of the present application provides a method for evaluating the importance of a drainage pipe node, comprising:

[0007] Constructing an adjacency matrix and a simulation model corresponding to the drainage network, wherein the adjacency matrix is ​​used to indicate the topological relationship between multiple drainage nodes and drainage pipes in the drainage network;

[0008] Based on the adjacency matrix, determining a plurality of nodes to be optimized from the drainage nodes;

[0009] Optimizing the plurality of nodes to be optimized, using the simulation model to obtain an importance parameter of each node to be optimized;

[0010] According to the importance parameters corresponding to the multiple nodes to be optimized, importance evaluation is performed on the multiple nodes to be optimized.

[0011] In a possible implementation, determining a plurality of nodes to be optimized from the drain nodes based on the adjacency matrix includes:

[0012] Determining the connection relationship between each drainage node and other drainage nodes according to the topological relationship of multiple drainage nodes in the drainage network;

[0013] Determine an elevation map corresponding to the drainage network, and determine the elevation value of each drainage node based on the elevation map;

[0014] The multiple nodes to be optimized are determined from the multiple drainage nodes according to the connection relationship between the multiple drainage nodes, the elevation value of each drainage node and the optimization parameters.

[0015] In a possible implementation, determining the plurality of nodes to be optimized from the plurality of drainage nodes according to the connection relationship between the plurality of drainage nodes, the elevation value of each drainage node, and the optimization parameter includes:

[0016] For any one of the plurality of drainage nodes, determining a related node of the drainage node according to a connection relationship between the drainage node and other drainage nodes, wherein the related node is a node having a connection relationship with the drainage node;

[0017] Determining an elevation parameter of the drainage node according to the elevation values ​​of the drainage node and the related node, wherein the elevation parameter is used to indicate an elevation difference of the drainage node relative to the related node;

[0018] According to the connection relationship between the multiple drainage nodes, the elevation parameters of each drainage node and the optimization parameters, the multiple nodes to be optimized are determined from the multiple drainage nodes, wherein the optimization parameters are determined according to the multiple catchment areas in the drainage network.

[0019] In a possible implementation manner, the optimizing process for the plurality of nodes to be optimized and using the simulation model to obtain the importance parameter of each node to be optimized includes:

[0020] Determine the hierarchical codes corresponding to the multiple nodes to be optimized;

[0021] Determining importance evaluation indicators corresponding to a plurality of nodes to be optimized according to the simulation model;

[0022] According to the hierarchical codes and importance evaluation indicators corresponding to the multiple nodes to be optimized, importance parameters corresponding to the multiple nodes to be optimized are determined.

[0023] In a possible implementation, the drainage nodes include multiple key nodes, and the multiple importance evaluation indicators of the nodes to be optimized are determined according to the simulation model, including:

[0024] According to the simulation model, determining the flow mean corresponding to each key node in multiple preset time periods and the first flow parameter corresponding to the target preset time period;

[0025] For any one of the multiple nodes to be optimized, based on the node to be optimized, the simulation model is optimized, and according to the optimized simulation model, a second flow parameter corresponding to each key node within the target preset time period is determined;

[0026] Based on the flow mean, the first flow parameter and the second flow parameter, determine the Nash efficiency coefficient corresponding to each key node, and determine the mean value of the Nash efficiency coefficients of the multiple key nodes;

[0027] The average value of the Nash efficiency coefficients of the multiple key nodes is used as the importance evaluation index corresponding to the node to be optimized.

[0028] In a possible implementation manner, the number of nodes to be optimized is M, and the method further includes:

[0029] Determine X optimization ratios, and for any one of the X optimization ratios, determine a quantity parameter N corresponding to the optimization ratio, wherein the optimization ratio is used to indicate a ratio of the number of optimization nodes to the total number of drainage nodes, wherein X, N, and M are positive integers greater than 0, and M>N;

[0030] Determining N optimization nodes from the M nodes to be optimized according to the importance parameters of the M nodes to be optimized;

[0031] Based on the N optimization nodes, the simulation model is optimized to obtain a candidate simulation model corresponding to the optimization ratio;

[0032] A drainage scenario is simulated for X candidate simulation models to obtain corresponding simulation time consumption and Nash efficiency coefficients. A target simulation model is determined from the X candidate simulation models according to the simulation time consumption and Nash efficiency coefficients corresponding to the X candidate simulation models, and the target simulation model is used as the optimized simulation model.

[0033] In a possible implementation, the simulation model is optimized based on the N optimization nodes to obtain a candidate simulation model corresponding to the optimization ratio, including:

[0034] For any one of the N optimization nodes, determine the upstream pipeline information, upstream flow information, downstream pipeline information, and downstream flow information of the optimization node;

[0035] According to the upstream pipeline information, upstream flow information, downstream pipeline information, and downstream flow information of the optimization node, the optimization node is optimized to obtain a corresponding optimized pipeline;

[0036] Based on the optimization pipeline and simulation model corresponding to each optimization node, a candidate simulation model corresponding to the optimization ratio is obtained.

[0037] In a second aspect, an embodiment of the present application provides a drainage pipe node importance evaluation device, comprising: a construction module, for constructing an adjacency matrix and a simulation model corresponding to a drainage pipe network, wherein the adjacency matrix is ​​used to indicate a topological relationship between a plurality of drainage nodes and drainage pipes in the drainage pipe network;

[0038] A processing module, used for determining a plurality of nodes to be optimized from the drainage nodes based on the adjacency matrix;

[0039] The processing module is further used to perform optimization processing on the plurality of nodes to be optimized, and obtain the importance parameter of each node to be optimized by using the simulation model;

[0040] An evaluation module is used to evaluate the importance of the multiple nodes to be optimized according to the importance parameters corresponding to the multiple nodes to be optimized.

[0041] In a possible implementation, the processing module is also used to determine the connection relationship between each drainage node and other drainage nodes based on the topological relationship of multiple drainage nodes in the drainage network; determine the elevation map corresponding to the drainage network, and determine the elevation value of each drainage node based on the elevation map; determine the multiple nodes to be optimized from the multiple drainage nodes based on the connection relationship between the multiple drainage nodes, the elevation value of each drainage node and the optimization parameters.

[0042] In a possible implementation, the processing module is also used to determine, for any one of the multiple drainage nodes, a related node of the drainage node based on a connection relationship between the drainage node and other drainage nodes, wherein a related node is a node that has a connection relationship with the drainage node; determine an elevation parameter of the drainage node based on elevation values ​​of the drainage node and the related node, wherein the elevation parameter is used to indicate an elevation difference between the drainage node and the related node; determine the multiple nodes to be optimized from the multiple drainage nodes based on the connection relationship between the multiple drainage nodes, the elevation parameter of each drainage node and the optimization parameter, wherein the optimization parameter is determined based on the multiple catchment areas in the drainage network.

[0043] In a possible implementation, the processing module is also used to determine the hierarchical codes corresponding to the multiple nodes to be optimized; determine the importance evaluation indicators corresponding to the multiple nodes to be optimized based on the simulation model; and determine the importance parameters corresponding to the multiple nodes to be optimized based on the hierarchical codes and importance evaluation indicators corresponding to the multiple nodes to be optimized.

[0044] In a possible implementation, the drainage node includes multiple key nodes, and the processing module is also used to determine the flow mean corresponding to each key node in multiple preset time periods and the first flow parameter corresponding to the target preset time period according to the simulation model; for any one of the multiple nodes to be optimized, based on the node to be optimized, the simulation model is optimized, and the second flow parameter corresponding to each key node in the target preset time period is determined according to the optimized simulation model; based on the flow mean, the first flow parameter and the second flow parameter, the Nash efficiency coefficient corresponding to each key node is determined, and the average Nash efficiency coefficient of the multiple key nodes is determined; the average Nash efficiency coefficient of the multiple key nodes is used as the importance evaluation index corresponding to the node to be optimized.

[0045] In a possible implementation manner, the number of nodes to be optimized is M, and the device further includes an optimization module;

[0046] The optimization module is used to determine X optimization ratios, and for any one of the X optimization ratios, determine a quantity parameter N corresponding to the optimization ratio, wherein the optimization ratio is used to indicate the ratio of the number of optimization nodes to the total number of drainage nodes, wherein X, N and M are positive integers greater than 0, and M>N; determine N optimization nodes from the M nodes to be optimized according to the importance parameters of the M nodes to be optimized; optimize the simulation model based on the N optimization nodes to obtain a candidate simulation model corresponding to the optimization ratio; simulate the drainage scenario for the X candidate simulation models to obtain the corresponding simulation time consumption and Nash efficiency coefficient; determine a target simulation model from the X candidate simulation models according to the simulation time consumption and Nash efficiency coefficient corresponding to the X candidate simulation models, and use the target simulation model as the optimized simulation model.

[0047] In a possible implementation, the optimization module is also used to determine the upstream pipeline information, upstream flow information, downstream pipeline information, and downstream flow information of any one of the N optimization nodes; optimize the optimization node according to the upstream pipeline information, upstream flow information, downstream pipeline information, and downstream flow information of the optimization node to obtain the corresponding optimized pipeline; based on the optimized pipeline and simulation model corresponding to each optimization node, obtain the candidate simulation model corresponding to the optimization ratio.

[0048] In a third aspect, an embodiment of the present application provides a drainage pipe node importance assessment device, including: a memory, a processor;

[0049] The memory stores computer-executable instructions;

[0050] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0051] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementations of the first aspect.

[0052] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementation methods of the first aspect.

[0053] The embodiments of the present application provide a method, device, equipment and medium for evaluating the importance of drainage pipe nodes. The method determines the nodes to be optimized through the topological relationship between the drainage nodes and pipes in the drainage network, and then determines the importance parameters corresponding to the nodes to be optimized based on the simulation model of the drainage pipe, thereby realizing the evaluation of the importance of the drainage pipe nodes and determining the importance of the nodes to be optimized and the node information corresponding to the nodes to be optimized in the drainage pipe. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0055] Figure 1 A schematic diagram of a method for evaluating the importance of drainage network nodes provided in an embodiment of the present application Figure 1 ;

[0056] Figure 2 A schematic diagram of a method for evaluating the importance of drainage network nodes provided in an embodiment of the present application Figure 2 ;

[0057] Figure 3 A schematic diagram of a method for evaluating the importance of drainage network nodes provided in an embodiment of the present application Figure 3 ;

[0058] Figure 4 A schematic diagram comparing the computational efficiency and node Nash efficiency coefficients of candidate simulation models corresponding to different optimization ratios provided in the embodiment of the present application;

[0059] Figure 5 A schematic diagram of the structure of a drainage pipe node importance device provided in this application;

[0060] Figure 6A schematic diagram of the structure of a drainage pipe node importance assessment device provided in this application.

[0061] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0062] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0063] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0064] "Multiple" means two or more, and other quantifiers are similar. "And / or" describes the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.

[0065] In the embodiments of the present application, the words "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0066] The urban drainage network system is an important urban infrastructure and a key project for urban pollution prevention and control and urban drainage and waterlogging prevention. An urban drainage system simulation model is established to simulate the urban drainage process and the water flow conditions in each part of the drainage pipe in order to manage and control the drainage network system.

[0067] At present, based on the urban drainage system simulation model, it is possible to simulate the urban drainage process under different design or operating conditions, provide decision support for flood control emergency response, intelligent control, etc., and then assist in optimizing the design of the drainage system and formulating effective operation plans.

[0068] However, due to the large number of drainage nodes and pipes in the urban drainage system and the complex topological structure, the calculation of the urban drainage system model is extremely time-consuming, so that design optimization is difficult to achieve due to the time-consuming process; the operation plan cannot meet the timeliness requirements of real-time operation.

[0069] In response to the above problems, the present application provides a drainage network node importance assessment method. The method determines the importance parameters of the node to be optimized by comparing the simulation model with the simulation model obtained by optimizing the node to be optimized, thereby realizing the evaluation of the importance of the drainage pipe node and determining the importance of the node to be optimized and the node information corresponding to the node to be optimized in the drainage pipe.

[0070] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0071] Figure 1 A schematic diagram of a method for evaluating the importance of drainage network nodes provided in an embodiment of the present application Figure 1 .like Figure 1 As shown, the method includes:

[0072] S101, constructing an adjacency matrix and a simulation model corresponding to the drainage network.

[0073] The adjacency matrix is ​​used to indicate the topological relationship between multiple drainage nodes and drainage pipes in the drainage network. For example, the drainage nodes may be inspection wells, discharge outlets, storage units, and the like.

[0074] The adjacency matrix is ​​constructed in the following way:

[0075]

[0076]

[0077]

[0078]

[0079] in, Represents a collection of drainage network nodes and pipes; represents a collection of drainage nodes; Represents a collection of drainage pipes; represents the adjacency matrix representing the topological relationship between drainage nodes and drainage pipes; Indicates the connection relationship between nodes, 0 means no connection, and 1 means connection.

[0080] The sub-catchment area is divided according to the actual situation of the drainage network in the area where the drainage system is located. The data of the topological structure and geographical attribute information of the drainage network are organized into the input file format of the Storm Water Management Model (SWMM), and the simulation model is calibrated in combination with the monitored flow data, water quality data, etc.

[0081] S102: Based on the adjacency matrix, determine a plurality of nodes to be optimized from the drainage nodes.

[0082] The nodes to be optimized are nodes in the drainage nodes that can be optimized, and the optimization process is to merge the nodes to be optimized and optimize the simulation model.

[0083] According to the adjacency matrix that characterizes the topological relationship between the drainage nodes and the drainage pipes, the nodes that can be optimized are determined from the drainage nodes, where the nodes to be optimized can be, for example, discharge outlets; sub-catchment area exit points and starting points; intersection nodes; nodes with large differences in slopes of adjacent pipes, etc.

[0084] S103, performing optimization processing on the plurality of nodes to be optimized, using the simulation model to obtain an importance parameter of each node to be optimized.

[0085] Among them, the importance parameter is an indicator for evaluating the importance of the node to be optimized in the simulation model. The larger the importance parameter is, the greater the simulation error of the simulation model obtained after the corresponding node to be optimized is after optimization.

[0086] Each node to be optimized is optimized one by one to obtain the optimized simulation model, and the simulation error is determined according to the simulation parameter difference corresponding to the constructed initial simulation model and the simulation parameters of the optimized simulation model. According to the simulation error, the importance parameter of each node to be optimized is determined.

[0087] S104: Evaluate the importance of the multiple nodes to be optimized according to the importance parameters corresponding to the multiple nodes to be optimized.

[0088] The larger the importance parameter of the node to be optimized is, the higher the importance of the node to be optimized in the simulation model is. Therefore, the importance of multiple nodes to be optimized in the simulation model is evaluated according to the importance parameters of the nodes to be optimized.

[0089] An embodiment of the present application provides a method for evaluating the importance of drainage network nodes. The method determines the nodes to be optimized through the topological relationship between the drainage nodes and pipes in the drainage network, and then determines the importance parameters corresponding to the nodes to be optimized based on a simulation model of the drainage pipe, thereby realizing the evaluation of the importance of the drainage pipe nodes and determining the importance of the nodes to be optimized and the node information corresponding to the nodes to be optimized in the drainage pipe.

[0090] Figure 2 A schematic diagram of a method for evaluating the importance of drainage network nodes provided in an embodiment of the present application Figure 2 ,like Figure 2 As shown, in this embodiment Figure 1 Based on the embodiment, a possible implementation method of determining multiple nodes to be optimized from the drainage nodes based on the adjacency matrix is ​​described in detail. The method includes:

[0091] S201. Determine the connection relationship between each drainage node and other drainage nodes according to the topological relationship of multiple drainage nodes in the drainage network.

[0092] According to the adjacency matrix of the drainage network, based on Figure 1 The embodiment determines the adjacency matrix, and determines the connection relationship between the nodes according to each element in the adjacency matrix, wherein: Indicates the connection relationship between nodes, 0 means no connection, and 1 means connection.

[0093] S202: Determine an elevation map corresponding to the drainage network, and determine the elevation value of each drainage node based on the elevation map.

[0094] For example, the elevation map corresponding to the drainage network can be determined through network acquisition and the elevation value corresponding to each drainage node can be determined based on the elevation map.

[0095] S203: For any one of the multiple drainage nodes, determine the related nodes of the drainage node according to the connection relationship between the drainage node and other drainage nodes.

[0096] Among them, the drainage nodes that have a connection relationship are related nodes.

[0097] For any of the multiple drainage nodes, when two drainage nodes are connected, the related nodes are determined. It is determined that there is a connection relationship between drainage node 1 and drainage node 3, and then drainage node 3 is a related node of drainage node 1.

[0098] S204: Determine the elevation parameter of the drainage node according to the elevation values ​​of the drainage node and the related nodes.

[0099] The elevation parameter is used to indicate the elevation difference of the drainage node relative to the related nodes.

[0100] Based on the elevation map, the elevation value between the drainage node and the corresponding related node is determined, and the elevation difference of the drainage node relative to the related node is determined.

[0101] S205. Determine the multiple nodes to be optimized from the multiple drainage nodes according to the connection relationship between the multiple drainage nodes, the elevation parameter of each drainage node and the optimization parameter.

[0102] Among them, the optimization parameters are determined according to multiple catchment areas in the drainage network.

[0103] a. Determine the slope between the nodes according to the elevation parameters between the drainage node and the related nodes corresponding to the drainage node. If the slope reaches the set value, it means that the drainage node with a large difference in the slope of the adjacent pipelines of the drainage node is a non-optimizable node;

[0104] b. According to the adjacency matrix of the drainage network, when the sum of the element values ​​in the i-th row of the matrix is ​​not less than 2, it indicates that the i-th drainage node is an intersection point, and the intersection point is a non-optimizable node;

[0105] c. According to the multiple catchment areas in the drainage network, determine the sub-catchment area exit point, starting point and discharge outlet. The catchment area exit point, starting point and discharge outlet are non-optimizable nodes.

[0106] A plurality of unoptimizable nodes are eliminated from the drainage nodes, and a plurality of nodes to be optimized are determined from the drainage nodes.

[0107] An embodiment of the present application provides a method for evaluating the importance of drainage network nodes. The method determines the connection relationship between the drainage node and other drainage nodes and the elevation map of the drainage network, determines multiple nodes to be optimized in the drainage pipe, provides a basis for evaluating the importance of the nodes to be optimized, and improves the accuracy of the importance evaluation of the nodes to be optimized.

[0108] Figure 3 A schematic diagram of a method for evaluating the importance of drainage network nodes provided in an embodiment of the present application Figure 3 In this embodiment, the drainage nodes include multiple key nodes, and the key nodes may be, for example, non-optimizable nodes, nodes to be optimized with large importance parameters, etc. Figure 3 As shown, in this embodiment Figure 1 Example or Figure 2 Based on the embodiment, a possible implementation method of using the simulation model to optimize the multiple nodes to be optimized to obtain the importance parameter of each node to be optimized is described in detail. The method includes:

[0109] S301: Determine the hierarchical codes corresponding to multiple nodes to be optimized.

[0110] The following preset rules are used to determine the hierarchical codes corresponding to the multiple nodes to be optimized:

[0111] ① Each initial node (pipeline) without confluence is defined as a first-level node (pipeline), and the corresponding level code is 1.

[0112] ② When two first-level pipelines converge, a second-level pipeline is generated, and the corresponding pipeline and node level code is 2. When two pipelines of different levels converge into one pipeline, the level code of the composite pipeline is the higher level.

[0113] ③ Repeat step ② until all pipes and nodes in the entire system are counted.

[0114] ④ If multiple pipelines with the same level of coding are connected continuously, the hierarchy of these pipelines and nodes remains unchanged and they remain at the same level of coding.

[0115] S302. Determine, according to the simulation model, the flow mean corresponding to each key node in multiple preset time periods and the first flow parameter corresponding to the target preset time period.

[0116] The target preset time period is any one of a plurality of preset time periods.

[0117] Based on the simulation model, the drainage process is simulated to determine the flow mean of each key node in multiple preset time periods and the first flow parameter corresponding to any one of the multiple preset time periods.

[0118] S303. For any one of the multiple nodes to be optimized, based on the node to be optimized, the simulation model is optimized, and according to the optimized simulation model, a second flow parameter corresponding to each key node within the target preset time period is determined.

[0119] For any one of the multiple nodes to be optimized, based on the node to be optimized, the simulation model is optimized, the node to be optimized is merged to obtain an optimized simulation model, and based on the optimized simulation model, the drainage is simulated to obtain the second flow parameter corresponding to each key node within the target preset time period.

[0120] S304. Based on the traffic mean, the first traffic parameter and the second traffic parameter, determine the Nash efficiency coefficient corresponding to each key node, and determine the mean value of the Nash efficiency coefficients of the multiple key nodes.

[0121] Among them, the average value of the Nash efficiency coefficient of multiple key nodes is used to indicate the quality of the simulation performance of the optimized model.

[0122] The following formula is used to determine the Nash efficiency coefficient corresponding to each key node:

[0123]

[0124] in, is the Nash efficiency coefficient of key node j; is the second flow parameter; is the first flow parameter; Traffic mean.

[0125] The following formula is used to calculate the average Nash efficiency coefficient of multiple key nodes:

[0126]

[0127] Among them, M is the number of key nodes.

[0128] S305: Using the average value of the Nash efficiency coefficients of the multiple key nodes as an importance evaluation index corresponding to the node to be optimized.

[0129] The average value of the Nash efficiency coefficients of multiple key nodes, that is, the Nash efficiency coefficient corresponding to the simulation model after the node to be optimized is used as the importance evaluation index of the node to be optimized.

[0130] S306: Determine importance parameters corresponding to the multiple nodes to be optimized according to the hierarchical codes and importance evaluation indicators corresponding to the multiple nodes to be optimized.

[0131] The following formula is used to determine the importance parameter corresponding to each node to be optimized:

[0132]

[0133] in, represents the importance parameter of drainage node i; represents the level code of drainage node i; Represents the importance evaluation index of the node i to be optimized.

[0134] In a possible implementation, the number of nodes to be optimized is M. After evaluating the importance of the multiple nodes to be optimized according to the importance parameters corresponding to the multiple nodes to be optimized, the simulation model can also be optimized based on the importance parameters of the multiple nodes to be optimized. The specific process is as follows:

[0135] Determine X optimization ratios, and for any one of the X optimization ratios, determine a quantity parameter N corresponding to the optimization ratio, wherein X, N, and M are positive integers greater than 0, and M>N;

[0136] The optimization ratio is used to indicate the ratio of the number of optimized nodes to the total number of drainage nodes, for example, it can be 20%, 40%, etc. The optimized nodes are determined from multiple nodes to be optimized according to the optimization ratio based on the importance parameter. The quantity parameter is the number of optimized nodes.

[0137] Determine X optimization ratios, each of which corresponds to an optimization scheme. According to the optimization ratio and the total number of drainage nodes, determine the number of optimization nodes corresponding to the optimization ratio. For example, if the total number of drainage nodes is 100, determine two optimization ratios of 20% and 30% respectively. Then the corresponding number parameters N are 20 and 30 respectively.

[0138] Determining N optimization nodes from the M nodes to be optimized according to the importance parameters of the M nodes to be optimized;

[0139] Since the greater the importance parameter of the node to be optimized, the greater the corresponding simulation error after optimization, the lower the optimization priority. Therefore, according to the importance parameter of the node to be optimized, the M nodes to be optimized are sorted to obtain a priority sequence. According to the quantity parameter N and the priority sequence, the N optimization nodes with the lowest priority are determined from the M nodes to be optimized.

[0140] Based on the N optimization nodes, the simulation model is optimized to obtain a candidate simulation model corresponding to the optimization ratio;

[0141] Among them, the simulation model after optimization is the candidate simulation model.

[0142] Based on the N optimized nodes determined by the optimization ratio, the N nodes to be optimized are merged to achieve optimization processing of the simulation model, and a candidate simulation model corresponding to the optimization ratio is obtained.

[0143] A drainage scenario is simulated for X candidate simulation models to obtain corresponding simulation time consumption and Nash efficiency coefficients. A target simulation model is determined from the X candidate simulation models according to the simulation time consumption and Nash efficiency coefficients corresponding to the X candidate simulation models, and the target simulation model is used as the optimized simulation model.

[0144] Among them, the simulation time is the time required to complete a drainage scenario simulation; the Nash efficiency coefficient is used to indicate the quality of the simulation results of the candidate simulation model; the target simulation model is the candidate simulation model with the best simulation effect among the X candidate simulation models.

[0145] Simulate the drainage scenario for X candidate simulation models. After the simulation is completed, obtain the simulation time corresponding to each candidate simulation model and the Nash efficiency coefficient indicating the quality of the simulation results of the candidate simulation model. Consider the simulation time and the Nash efficiency coefficient comprehensively. Take the average value of the Nash efficiency coefficients of multiple key nodes as the Nash efficiency coefficient of the candidate simulation model. Determine a candidate simulation model with the best simulation effect from the X candidate simulation models as the target simulation model, and use the target simulation model as the optimized simulation model.

[0146] The simulation model is optimized, and the optimized simulation model effectively reduces the simulation time of urban drainage scenarios and improves the practicability and timeliness of the simulation model. The simulation model is optimized based on the importance of the nodes to be optimized, emphasizing the importance of the nodes to be optimized, avoiding the loss of information on key nodes, and reducing the simulation error of the optimized simulation model.

[0147] Figure 4 A schematic diagram showing the comparison of the computational efficiency and node Nash efficiency coefficient of candidate simulation models corresponding to different optimization ratios provided in the embodiment of the present application. The horizontal axis is the optimization ratio, and the vertical axis is the node Nash efficiency coefficient and the percentage of simulation time reduction. Figure 4 As shown in the figure, the larger the optimization ratio is, that is, the more nodes are optimized, the more the simulation time of the corresponding candidate simulation model is reduced, and the simulation time is reduced; the Nash efficiency coefficient of node N2 changes suddenly when the optimization ratio is greater than 30%, and drops sharply. Therefore, when the optimization ratio is not greater than 30%, the simulation effect of node N2 is better.

[0148] In a possible implementation, based on N optimization nodes, serial pipes with the same material are merged to optimize the simulation model. Since serial pipes with the same material are merged, the roughness coefficient n of the merged pipe is equal to that of the original pipe. A possible implementation of optimizing the simulation model based on N optimization nodes to obtain a candidate simulation model corresponding to the optimization ratio is described in detail, including:

[0149] For any one of the N optimization nodes, determine the upstream pipeline information, upstream flow information, downstream pipeline information, and downstream flow information of the optimization node;

[0150] Among them, the pipeline information includes the pipeline length and the pipe bottom elevation value; the flow information is the maximum flow.

[0151] Determine the pipe length, pipe bottom elevation value, and maximum flow rate of the upstream pipeline and the pipe length, pipe bottom elevation value, and maximum flow rate of the downstream pipeline of each optimization node.

[0152] According to the upstream pipeline information, upstream flow information, downstream pipeline information, and downstream flow information of the optimization node, the optimization node is optimized to obtain a corresponding optimized pipeline;

[0153] Among them, based on the optimization node, the pipeline obtained by merging the upstream pipeline and the downstream pipeline of the optimization node is the optimized pipeline.

[0154] According to the pipe length and pipe bottom elevation of the upstream pipe and the pipe length and pipe bottom elevation of the downstream pipe at the optimization node, the slope of the optimized pipe is calculated using the following formula: :

[0155]

[0156] in, To optimize the bottom elevation of the upstream pipeline of the node; To optimize the bottom elevation of the pipeline downstream of the node; To optimize the pipe length of the upstream pipe of the node; To optimize the pipe length of the downstream pipe of the node.

[0157] The characteristic of series pipelines is that the flow rate of each pipe section is equal. According to the Darcy-Weisbach equation, when the flow rate and other conditions remain unchanged, the resistance head loss along the pipeline is inversely proportional to the fifth power of the pipe diameter:

[0158]

[0159] in, is the head loss of the pipe section; L is the length of the pipe; D is the diameter of the pipe.

[0160] According to the characteristic that the total head loss of the series pipeline is equal to the sum of the head losses of each pipe section, the shape parameters of the pipeline corresponding to the optimization node are determined, and based on the shape parameters, the optimized pipeline is obtained. The calculation formula used is as follows:

[0161]

[0162] in, To optimize the length of the pipeline; and are the upstream and downstream pipeline lengths before optimization, respectively; To optimize the diameter of the pipe; and are the upstream and downstream pipe diameters before optimization, respectively.

[0163] According to the optimization pipeline and simulation model corresponding to each optimization node, a candidate simulation model corresponding to the optimization ratio is obtained.

[0164] The upstream pipeline and the downstream pipeline of the optimization node are replaced with the optimized pipeline, and the optimized simulation model, that is, the candidate simulation model, is obtained according to the optimized pipeline and the simulation model before optimization.

[0165] An embodiment of the present application provides a method for evaluating the importance of drainage network nodes and optimizing the model. The method simulates the urban drainage process of a simulation model, calculates the average flow rate corresponding to each node to be optimized in multiple preset time periods and the first flow parameter in a target preset time period, and then optimizes the multiple nodes to be optimized one by one. According to the optimized simulation model, the second flow parameter corresponding to each other node to be optimized in the target preset time period is determined, and the Nash efficiency average of each node to be optimized is calculated. According to the hierarchical coding of the nodes to be optimized and the Nash efficiency average, the importance parameters corresponding to the multiple nodes to be optimized are determined, thereby realizing the evaluation of the importance of drainage pipe nodes and determining the importance of the nodes to be optimized and the node information corresponding to the nodes to be optimized in the drainage pipe.

[0166] Figure 5 A schematic diagram of the structure of a drainage pipe node importance device provided in this application, such as Figure 5 As shown, a drainage pipe node importance device 50 provided in this embodiment includes:

[0167] A construction module 501 is used to construct an adjacency matrix and a simulation model corresponding to the drainage network, where the adjacency matrix is ​​used to indicate the topological relationship between multiple drainage nodes and drainage pipes in the drainage network;

[0168] A processing module 502 is used to determine a plurality of nodes to be optimized from the draining nodes based on the adjacency matrix;

[0169] The processing module 502 is also used to optimize the multiple nodes to be optimized, and obtain the importance parameter of each node to be optimized by using a simulation model;

[0170] The evaluation module 503 is used to evaluate the importance of the multiple nodes to be optimized according to the importance parameters corresponding to the multiple nodes to be optimized.

[0171] In a possible implementation, the processing module 502 is also used to determine the connection relationship between each drainage node and other drainage nodes based on the topological relationship of multiple drainage nodes in the drainage network; determine the elevation map corresponding to the drainage network, and determine the elevation value of each drainage node based on the elevation map; determine multiple nodes to be optimized from multiple drainage nodes based on the connection relationship between multiple drainage nodes, the elevation value of each drainage node and the optimization parameters.

[0172] In a possible implementation, the processing module 502 is also used to determine, for any one of the multiple drainage nodes, a related node of the drainage node based on a connection relationship between the drainage node and other drainage nodes, wherein the related node is a node that has a connection relationship with the drainage node; determine an elevation parameter of the drainage node based on elevation values ​​of the drainage node and the related node, wherein the elevation parameter is used to indicate the elevation difference of the drainage node relative to the related node; determine a plurality of nodes to be optimized from the multiple drainage nodes based on the connection relationship between the multiple drainage nodes, the elevation parameter of each drainage node, and an optimization parameter, wherein the optimization parameter is determined based on a plurality of catchment areas within the drainage network.

[0173] In a possible implementation, the processing module 502 is also used to determine the hierarchical codes corresponding to the multiple nodes to be optimized; determine the importance evaluation indicators corresponding to the multiple nodes to be optimized based on the simulation model; and determine the importance parameters corresponding to the multiple nodes to be optimized based on the hierarchical codes and importance evaluation indicators corresponding to the multiple nodes to be optimized.

[0174] In a possible implementation, the drainage node includes multiple key nodes, and the processing module 502 is also used to determine the flow mean corresponding to each key node in multiple preset time periods and the first flow parameter corresponding to the target preset time period according to the simulation model; for any one of the multiple nodes to be optimized, based on the node to be optimized, the simulation model is optimized, and the second flow parameter corresponding to each key node in the target preset time period is determined according to the optimized simulation model; based on the flow mean, the first flow parameter and the second flow parameter, the Nash efficiency coefficient corresponding to each key node is determined, and the mean of the Nash efficiency coefficients of multiple key nodes is determined; the mean of the Nash efficiency coefficients of multiple key nodes is used as the importance evaluation index corresponding to the node to be optimized.

[0175] In a possible implementation manner, the number of nodes to be optimized is M, and the device further includes an optimization module;

[0176] The optimization module is used to determine X optimization ratios, and for any one of the X optimization ratios, determine a quantity parameter N corresponding to the optimization ratio, where the optimization ratio is used to indicate the ratio of the number of optimization nodes to the total number of drainage nodes, wherein X, N and M are positive integers greater than 0, and M>N; determine N optimization nodes from the M nodes to be optimized according to the importance parameters of the M nodes to be optimized; optimize the simulation model based on the N optimization nodes to obtain a candidate simulation model corresponding to the optimization ratio; simulate the drainage scenario for the X candidate simulation models to obtain the corresponding simulation time consumption and Nash efficiency coefficient; determine a target simulation model from the X candidate simulation models according to the simulation time consumption and Nash efficiency coefficient corresponding to the X candidate simulation models, and use the target simulation model as the optimized simulation model.

[0177] In a possible implementation, the optimization module is also used to determine the upstream pipeline information, upstream flow information, downstream pipeline information, and downstream flow information of any optimization node among the N optimization nodes; optimize the optimization node according to the upstream pipeline information, upstream flow information, downstream pipeline information, and downstream flow information of the optimization node to obtain the corresponding optimized pipeline; based on the optimization pipeline and simulation model corresponding to each optimization node, obtain a candidate simulation model corresponding to the optimization ratio.

[0178] The present embodiment provides a drainage pipe node importance assessment device, which can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail in the present embodiment.

[0179] Figure 6 This is a schematic diagram of the structure of a drainage pipeline node importance assessment device provided in this application. Figure 6 As shown, the electronic device 60 provided in this embodiment includes: at least one processor 601 and a memory 602. Optionally, the device 60 also includes a communication component 603. The processor 601, the memory 602 and the communication component 603 are connected via a bus 604.

[0180] In a specific implementation process, at least one processor 601 executes the computer execution instructions stored in the memory 602, so that at least one processor 601 executes the above method.

[0181] The specific implementation process of the processor 601 can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0182] In the above embodiments, it should be understood that the processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the invention can be directly implemented as a hardware processor, or can be implemented by a combination of hardware and software modules in the processor.

[0183] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (NVM), such as at least one disk storage.

[0184] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0185] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0186] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0187] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0188] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0189] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0190] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0191] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0192] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0193] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other media that can store program codes.

[0194] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary technical means in the art not disclosed by the present invention, are not limited to the precise structure described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for evaluating the importance of drainage network nodes, characterized in that: include: Constructing an adjacency matrix and a simulation model corresponding to the drainage network, wherein the adjacency matrix is ​​used to indicate the topological relationship between multiple drainage nodes and drainage pipes in the drainage network; Based on the adjacency matrix, determining a plurality of nodes to be optimized from the drainage nodes; Optimizing the plurality of nodes to be optimized, using the simulation model to obtain an importance parameter of each node to be optimized; According to the importance parameters corresponding to the multiple nodes to be optimized, importance evaluation is performed on the multiple nodes to be optimized.

2. The method according to claim 1, characterized in that The step of determining a plurality of nodes to be optimized from the drainage nodes based on the adjacency matrix includes: Determining the connection relationship between each drainage node and other drainage nodes according to the topological relationship of multiple drainage nodes in the drainage network; Determine an elevation map corresponding to the drainage network, and determine the elevation value of each drainage node based on the elevation map; The multiple nodes to be optimized are determined from the multiple drainage nodes according to the connection relationship between the multiple drainage nodes, the elevation value of each drainage node and the optimization parameters.

3. The method according to claim 2, characterized in that The step of determining the plurality of nodes to be optimized from the plurality of drainage nodes according to the connection relationship between the plurality of drainage nodes, the elevation value of each drainage node and the optimization parameter comprises: For any one of the plurality of drainage nodes, determining a related node of the drainage node according to a connection relationship between the drainage node and other drainage nodes, wherein the related node is a node having a connection relationship with the drainage node; Determining an elevation parameter of the drainage node according to the elevation values ​​of the drainage node and the related node, wherein the elevation parameter is used to indicate an elevation difference of the drainage node relative to the related node; According to the connection relationship between the multiple drainage nodes, the elevation parameters of each drainage node and the optimization parameters, the multiple nodes to be optimized are determined from the multiple drainage nodes, wherein the optimization parameters are determined according to the multiple catchment areas in the drainage network.

4. The method according to claim 1, characterized in that: The step of performing optimization processing on the plurality of nodes to be optimized and using the simulation model to obtain the importance parameter of each node to be optimized includes: Determine the hierarchical codes corresponding to the multiple nodes to be optimized; Determining importance evaluation indicators corresponding to a plurality of nodes to be optimized according to the simulation model; According to the hierarchical codes and importance evaluation indicators corresponding to the multiple nodes to be optimized, importance parameters corresponding to the multiple nodes to be optimized are determined.

5. The method according to claim 4, characterized in that The drainage nodes include multiple key nodes. According to the simulation model, multiple importance evaluation indicators of the nodes to be optimized are determined, including: According to the simulation model, determining the flow mean corresponding to each key node in multiple preset time periods and the first flow parameter corresponding to the target preset time period; For any one of the multiple nodes to be optimized, based on the node to be optimized, the simulation model is optimized, and according to the optimized simulation model, a second flow parameter corresponding to each key node within the target preset time period is determined; Based on the flow mean, the first flow parameter and the second flow parameter, determine the Nash efficiency coefficient corresponding to each key node, and determine the mean value of the Nash efficiency coefficients of the multiple key nodes; The average value of the Nash efficiency coefficients of the multiple key nodes is used as the importance evaluation index corresponding to the node to be optimized.

6. The method according to claim 1, characterized in that The number of nodes to be optimized is M, and the method further includes: Determine X optimization ratios, and for any one of the X optimization ratios, determine a quantity parameter N corresponding to the optimization ratio, wherein the optimization ratio is used to indicate a ratio of the number of optimization nodes to the total number of drainage nodes, wherein X, N, and M are positive integers greater than 0, and M>N; Determining N optimization nodes from the M nodes to be optimized according to the importance parameters of the M nodes to be optimized; Based on the N optimization nodes, the simulation model is optimized to obtain a candidate simulation model corresponding to the optimization ratio; A drainage scenario is simulated for X candidate simulation models to obtain corresponding simulation time consumption and Nash efficiency coefficients. A target simulation model is determined from the X candidate simulation models according to the simulation time consumption and Nash efficiency coefficients corresponding to the X candidate simulation models, and the target simulation model is used as the optimized simulation model.

7. The method according to claim 6, characterized in that The step of optimizing the simulation model based on the N optimization nodes to obtain a candidate simulation model corresponding to the optimization ratio includes: For any one of the N optimization nodes, determine the upstream pipeline information, upstream flow information, downstream pipeline information, and downstream flow information of the optimization node; According to the upstream pipeline information, upstream flow information, downstream pipeline information, and downstream flow information of the optimization node, the optimization node is optimized to obtain a corresponding optimized pipeline; Based on the optimization pipeline and simulation model corresponding to each optimization node, a candidate simulation model corresponding to the optimization ratio is obtained.

8. A drainage pipeline node importance assessment device, characterized in that: include: A construction module, used to construct an adjacency matrix and a simulation model corresponding to the drainage network, wherein the adjacency matrix is ​​used to indicate the topological relationship between multiple drainage nodes and drainage pipes in the drainage network; A processing module, used for determining a plurality of nodes to be optimized from the drainage nodes based on the adjacency matrix; The processing module is further used to perform optimization processing on the plurality of nodes to be optimized, and obtain the importance parameter of each node to be optimized by using the simulation model; An evaluation module is used to evaluate the importance of the multiple nodes to be optimized according to the importance parameters corresponding to the multiple nodes to be optimized.

9. A drainage pipeline node importance assessment device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor executes the drainage pipe node importance assessment method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the drainage pipe node importance assessment method as described in any one of claims 1-7.

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