Digraph-based overflow analysis method, apparatus and device, and medium

Abstract

The invention relates to the technical field of data processing, and provides an overflow analysis method, device and equipment based on a directed graph and a medium, the directed graph of a pipe network of a to-be-analyzed area can be constructed according to monitoring nodes of the to-be-analyzed area, node analysis is performed on the directed graph to obtain configuration nodes, flow monitoring equipment is installed on the configuration nodes, and the flow monitoring equipment is used for monitoring the flow of the to-be-analyzed area. The method comprises the following steps of: configuring nodes in a directed graph, and performing real-time traffic monitoring on the corresponding configuration nodes by using traffic monitoring equipment to obtain actual real-time traffic of each path in the directed graph, so that optimal equipment installation nodes can be reasonably configured based on the directed graph to realize effective monitoring on regional traffic; and deducing the real-time flow of each path in the directed graph by adopting a preset flow algorithm to serve as the predicted real-time flow of each path, and carrying out overflow analysis according to the actual real-time flow of each path and the predicted real-time flow of each path to obtain an overflow analysis result of the to-be-analyzed region, so that accurate overflow analysis of the regional flow is realized.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to an overflow analysis method, device, equipment and medium based on a directed graph. Background Art

[0002] Flow monitoring and analysis of urban pipe networks is of great significance for ensuring urban safety, protecting the environment, improving management levels, and coping with urban waterlogging.

[0003] However, there is currently no reasonable method for overflow analysis, which leads to problems such as pipeline aging and water pollution due to inaccurate analysis and untimely response. At the same time, it also has a negative impact on the city's flood control and drainage, environmental protection and residents' living standards. Summary of the invention

[0004] In view of the above, it is necessary to provide a directed graph-based overflow analysis method, device, equipment and medium to solve the problem of inaccurate overflow analysis.

[0005] A directed graph-based overflow analysis method, the directed graph-based overflow analysis method comprising:

[0006] In response to an overflow analysis instruction for a region to be analyzed, obtaining a monitoring node of the region to be analyzed;

[0007] Constructing a directed graph of the pipe network of the area to be analyzed according to the monitoring nodes;

[0008] Performing node analysis on the directed graph to obtain configuration nodes;

[0009] Installing a flow monitoring device on the configuration node, and using the flow monitoring device to perform real-time flow monitoring on the corresponding configuration node to obtain the actual real-time flow of each path in the directed graph;

[0010] Using a preset traffic algorithm to deduce the real-time traffic of each path in the directed graph as the predicted real-time traffic of each path;

[0011] An overflow analysis is performed based on the actual real-time flow of each path and the predicted real-time flow of each path to obtain an overflow analysis result of the area to be analyzed.

[0012] According to a preferred embodiment of the present invention, constructing a directed graph of the pipe network of the area to be analyzed according to the monitoring nodes comprises:

[0013] Constructing the directed graph according to the pipe network structure and flow direction of the area to be analyzed;

[0014] Wherein, each monitoring node in the directed graph is identified;

[0015] Wherein, additional information is added to each graph node in the directed graph and a weight is added to each edge;

[0016] The additional information includes a combination of one or more of the following information: location information, historical traffic data, maintenance status, and equipment capacity of each graph node;

[0017] The weight of each edge is determined according to the flow capacity and pipe diameter of each edge.

[0018] According to a preferred embodiment of the present invention, performing node analysis on the directed graph to obtain configuration nodes comprises:

[0019] Obtain each cross node in the directed graph, and obtain the in-degree and out-degree of each cross node, calculate the sum of the in-degree of each cross node and the out-degree of each cross node to obtain the flow of each cross node, obtain a pre-configured flow threshold, and obtain the cross node whose calculated flow is greater than or equal to the flow threshold as a flow hub;

[0020] Analyzing the directed graph based on a preset path analysis algorithm to obtain a path intermediate point; wherein after removing the path intermediate point, the corresponding flow path is interrupted;

[0021] The directed graph is analyzed based on a preset cut point algorithm to obtain vulnerable nodes; wherein after deleting the vulnerable nodes, the connectivity between other graph nodes in the directed graph except the vulnerable nodes is reduced;

[0022] Performing cluster analysis on the traffic hubs, the path intermediate points and the vulnerable nodes to obtain each class;

[0023] Get the centroid of each class as the configuration node.

[0024] According to a preferred embodiment of the present invention, before using the traffic monitoring device to perform real-time traffic monitoring on the corresponding configuration node, the method further includes:

[0025] Obtaining historical monitoring parameters of the flow monitoring device;

[0026] Calculating statistical values ​​of the historical monitoring parameters;

[0027] The flow monitoring device is initialized according to the statistical value.

[0028] According to a preferred embodiment of the present invention, the overflow analysis is performed based on the actual real-time flow of each path and the predicted real-time flow of each path to obtain the overflow analysis result of the area to be analyzed, including:

[0029] Retrieving a pre-trained traffic anomaly detection model; wherein the traffic anomaly detection model is obtained by training based on a network model with classification function;

[0030] Based on the traffic anomaly detection model, a comparison and analysis is performed on the actual real-time traffic of each path and the predicted real-time traffic of each path to obtain the overflow analysis result.

[0031] According to a preferred embodiment of the present invention, after obtaining the overflow analysis result of the area to be analyzed, the method further includes:

[0032] When the overflow analysis result shows that there is a flow abnormality, generating an abnormality report according to the overflow analysis result, and sending the abnormality report to a designated terminal device; or

[0033] When the overflow analysis result shows that there is no flow abnormality, the real-time overflow analysis continues.

[0034] According to a preferred embodiment of the present invention, the method further comprises:

[0035] Configure the traffic warning line for each edge;

[0036] When the flow of any edge in the directed graph reaches the corresponding flow warning line, an alarm is issued and the current flow data of the arbitrary edge is recorded.

[0037] A directed graph-based overflow analysis device, the directed graph-based overflow analysis device comprising:

[0038] An acquisition unit, configured to acquire a monitoring node of the area to be analyzed in response to an overflow analysis instruction for the area to be analyzed;

[0039] A construction unit, configured to construct a directed graph of the pipe network of the area to be analyzed according to the monitoring nodes;

[0040] An analysis unit, used for performing node analysis on the directed graph to obtain configuration nodes;

[0041] A monitoring unit, configured to install a flow monitoring device on the configuration node, and use the flow monitoring device to perform real-time flow monitoring on the corresponding configuration node to obtain the actual real-time flow of each path in the directed graph;

[0042] A deduction unit, used for using a preset traffic algorithm to deduce the real-time traffic of each path in the directed graph as the predicted real-time traffic of each path;

[0043] The analysis unit is also used to perform overflow analysis based on the actual real-time flow of each path and the predicted real-time flow of each path to obtain the overflow analysis result of the area to be analyzed.

[0044] A computer device, comprising:

[0045] a memory storing at least one instruction; and

[0046] A processor executes the instructions stored in the memory to implement the directed graph-based overflow analysis method.

[0047] A computer-readable storage medium stores at least one instruction, and the at least one instruction is executed by a processor in a computer device to implement the directed graph-based overflow analysis method.

[0048] It can be seen from the above technical scheme that the present invention can construct a directed graph of the pipeline network of the area to be analyzed according to the monitoring nodes of the area to be analyzed, and perform node analysis on the directed graph to obtain configuration nodes, install flow monitoring equipment on the configuration nodes, and use the flow monitoring equipment to perform real-time flow monitoring on the corresponding configuration nodes to obtain the actual real-time flow of each path in the directed graph, so as to reasonably configure the optimal equipment installation nodes based on the directed graph to achieve effective monitoring of the regional flow; use a preset flow algorithm to deduce the real-time flow of each path in the directed graph as the predicted real-time flow of each path, and perform overflow analysis based on the actual real-time flow of each path and the predicted real-time flow of each path to obtain the overflow analysis result of the area to be analyzed, thereby achieving accurate overflow analysis of the regional flow. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a flow chart of a preferred embodiment of the overflow analysis method based on a directed graph of the present invention.

[0050] Figure 2 It is a functional module diagram of a preferred embodiment of the overflow analysis device based on a directed graph of the present invention.

[0051] Figure 3 It is a structural schematic diagram of a computer device of a preferred embodiment of the present invention for implementing the overflow analysis method based on a directed graph. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0053] like Figure 1 FIG. 1 is a flow chart of a preferred embodiment of the overflow analysis method based on directed graphs of the present invention. According to different requirements, the order of the steps in the flow chart can be changed, and some steps can be omitted.

[0054] The directed graph-based overflow analysis method is applied to one or more computer devices, wherein the computer device is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (ASIC), programmable gate arrays (FPGA), digital signal processors (DSP), embedded devices, etc.

[0055] The computer device may be any electronic product that can perform human-computer interaction with a user, such as a personal computer, a tablet computer, a smart phone, a personal digital assistant (PDA), a game console, an interactive network television (IPTV), a smart wearable device, etc.

[0056] The computer device may also include a network device and / or a user device, wherein the network device includes, but is not limited to, a single network server, a server group consisting of multiple network servers, or a cloud consisting of a large number of hosts or network servers based on cloud computing.

[0057] The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDN), as well as big data and artificial intelligence platforms.

[0058] Among them, Artificial Intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0059] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0060] The network where the computer device is located includes but is not limited to the Internet, a wide area network, a metropolitan area network, a local area network, a virtual private network (VPN), etc.

[0061] S10, in response to an overflow analysis instruction for a region to be analyzed, obtaining a monitoring node of the region to be analyzed.

[0062] In this embodiment, the area to be analyzed may be any area where water pipes are laid, such as a city.

[0063] In this embodiment, the overflow analysis instruction can be triggered according to actual overflow analysis requirements.

[0064] In this embodiment, the monitoring node may include an inspection well of the area to be analyzed, etc.

[0065] For example: rainwater enters the drainage system through the rainwater grate, and then flows into the inspection well connected to it. The inspection well collects and diverts rainwater to ensure the effective operation of the drainage system.

[0066] S11, constructing a directed graph of the pipe network in the area to be analyzed according to the monitoring nodes.

[0067] In this embodiment, constructing a directed graph of the pipe network of the area to be analyzed according to the monitoring nodes includes:

[0068] Constructing the directed graph according to the pipe network structure and flow direction of the area to be analyzed;

[0069] Wherein, each monitoring node in the directed graph is identified;

[0070] Wherein, additional information is added to each graph node in the directed graph and a weight is added to each edge;

[0071] The additional information includes a combination of one or more of the following information: location information, historical traffic data, maintenance status, and equipment capacity of each graph node;

[0072] The weight of each edge is determined according to the flow capacity and pipe diameter of each edge.

[0073] Among them, each monitoring node can be uniquely marked using different identifiers.

[0074] Among them, by adding additional information of different dimensions to each graph node, it is possible to facilitate comprehensive decision-making during overflow analysis to improve the accuracy of the analysis.

[0075] Among them, the weight of each edge is determined according to the flow capacity and pipe diameter of each edge, which helps to evaluate the flow efficiency of the flow.

[0076] For example, the directed graph can reflect the distribution of the city's underground pipe network.

[0077] S12, performing node analysis on the directed graph to obtain configuration nodes.

[0078] In this embodiment, performing node analysis on the directed graph to obtain configuration nodes includes:

[0079] Obtain each cross node in the directed graph, and obtain the in-degree and out-degree of each cross node, calculate the sum of the in-degree of each cross node and the out-degree of each cross node to obtain the flow of each cross node, obtain a pre-configured flow threshold, and obtain the cross node whose calculated flow is greater than or equal to the flow threshold as a flow hub;

[0080] Analyzing the directed graph based on a preset path analysis algorithm to obtain a path intermediate point; wherein after removing the path intermediate point, the corresponding flow path is interrupted;

[0081] The directed graph is analyzed based on a preset cut point algorithm to obtain vulnerable nodes; wherein after deleting the vulnerable nodes, the connectivity between other graph nodes in the directed graph except the vulnerable nodes is reduced;

[0082] Performing cluster analysis on the traffic hubs, the path intermediate points and the vulnerable nodes to obtain each class;

[0083] Get the centroid of each class as the configuration node.

[0084] The flow threshold can be configured according to the performance parameters of each monitoring node. By configuring the flow threshold, it is possible to screen out flow hubs with high flow. For example, the flow hub can be a busy intersection, including the confluence or bifurcation of major pipelines.

[0085] The preset path analysis algorithm may include, but is not limited to: Dijkstra algorithm, Floyd-Warshall algorithm. Through the graph path analysis algorithm, the key path affecting the overall flow can be found, thereby determining the path intermediate points that play an important role in multiple flow paths.

[0086] The preset cut point algorithm may be a Tarjan algorithm. The preset cut point algorithm can be used to query nodes with high connectivity in the directed graph.

[0087] Among them, density-based clustering algorithms such as K-means and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) can be used for clustering analysis, which can screen out key nodes and some nodes with large traffic as the best equipment installation locations.

[0088] S13, installing a flow monitoring device on the configuration node, and using the flow monitoring device to perform real-time flow monitoring on the corresponding configuration node to obtain the actual real-time flow of each path in the directed graph.

[0089] In this embodiment, the best node is selected to install the flow monitoring device, so that the device can be used to collect data more accurately.

[0090] In this embodiment, before using the traffic monitoring device to perform real-time traffic monitoring on the corresponding configuration node, the method further includes:

[0091] Obtaining historical monitoring parameters of the flow monitoring device;

[0092] Calculating statistical values ​​of the historical monitoring parameters;

[0093] The flow monitoring device is initialized according to the statistical value.

[0094] The statistical values ​​may include, but are not limited to: the mean and variance of each parameter.

[0095] Through the above embodiments, the device can be initialized based on the statistical values ​​of the historical monitoring parameters, so that the flow monitoring device can adapt to the normal flow state more quickly.

[0096] S14, using a preset traffic algorithm to deduce the real-time traffic of each path in the directed graph as the predicted real-time traffic of each path.

[0097] In this embodiment, the preset traffic algorithm may include, but is not limited to: Ford-Fulkerson algorithm and Edmonds-Karp algorithm.

[0098] In this embodiment, when performing traffic deduction, a network optimization algorithm (such as linear programming) may also be combined to more comprehensively evaluate the traffic distribution of different pipelines.

[0099] S15, performing overflow analysis according to the actual real-time flow of each path and the predicted real-time flow of each path to obtain the overflow analysis result of the area to be analyzed.

[0100] In this embodiment, the overflow analysis is performed according to the actual real-time flow of each path and the predicted real-time flow of each path to obtain the overflow analysis result of the area to be analyzed, including:

[0101] Retrieving a pre-trained traffic anomaly detection model; wherein the traffic anomaly detection model is obtained by training based on a network model with classification function;

[0102] Based on the traffic anomaly detection model, a comparison and analysis is performed on the actual real-time traffic of each path and the predicted real-time traffic of each path to obtain the overflow analysis result.

[0103] The network model with classification function may include, but is not limited to: support vector machine (SVM) and convolutional neural network (CNN).

[0104] The traffic anomaly detection model can be obtained by constructing training samples based on the traffic data of each graph node and each edge in the directed graph.

[0105] Through the above-mentioned embodiments, it is possible to automatically perform flow anomaly detection in combination with artificial intelligence means, and due to the reasonable deployment of flow monitoring equipment, the overflow analysis result is more accurate.

[0106] In this embodiment, after obtaining the overflow analysis result of the area to be analyzed, the method further includes:

[0107] When the overflow analysis result shows that there is a flow abnormality, generating an abnormality report according to the overflow analysis result, and sending the abnormality report to a designated terminal device; or

[0108] When the overflow analysis result shows that there is no flow abnormality, the real-time overflow analysis continues.

[0109] The designated terminal device may be a terminal device of a relevant operation and maintenance personnel, so as to remind the relevant personnel to handle the abnormality in a timely manner.

[0110] In this embodiment, the method further includes:

[0111] Configure the traffic warning line for each edge;

[0112] When the flow of any edge in the directed graph reaches the corresponding flow warning line, an alarm is issued and the current flow data of the arbitrary edge is recorded.

[0113] Through the above embodiment, it is possible to prevent the flow rate from exceeding the warning threshold. At the same time, when the warning threshold is exceeded, the current flow data of the corresponding edge is recorded for use in subsequent analysis.

[0114] It can be seen from the above technical scheme that the present invention can construct a directed graph of the pipeline network of the area to be analyzed according to the monitoring nodes of the area to be analyzed, and perform node analysis on the directed graph to obtain configuration nodes, install flow monitoring equipment on the configuration nodes, and use the flow monitoring equipment to perform real-time flow monitoring on the corresponding configuration nodes to obtain the actual real-time flow of each path in the directed graph, so as to reasonably configure the optimal equipment installation nodes based on the directed graph to achieve effective monitoring of the regional flow; use a preset flow algorithm to deduce the real-time flow of each path in the directed graph as the predicted real-time flow of each path, and perform overflow analysis based on the actual real-time flow of each path and the predicted real-time flow of each path to obtain the overflow analysis result of the area to be analyzed, thereby achieving accurate overflow analysis of the regional flow.

[0115] like Figure 2 As shown, it is a functional module diagram of a preferred embodiment of the overflow analysis device based on a directed graph of the present invention. The overflow analysis device 11 based on a directed graph includes an acquisition unit 110, a construction unit 111, an analysis unit 112, a monitoring unit 113, and a deduction unit 114. The module / unit referred to in the present invention refers to a series of computer program segments that can be executed by a processor and can perform fixed functions, which are stored in a memory. In this embodiment, the functions of each module / unit will be described in detail in subsequent embodiments.

[0116] The acquisition unit 110 is used to acquire the monitoring nodes of the area to be analyzed in response to the overflow analysis instruction of the area to be analyzed;

[0117] The construction unit 111 is used to construct a directed graph of the pipe network of the area to be analyzed according to the monitoring nodes;

[0118] The analysis unit 112 is used to perform node analysis on the directed graph to obtain configuration nodes;

[0119] The monitoring unit 113 is used to install a flow monitoring device on the configuration node, and use the flow monitoring device to perform real-time flow monitoring on the corresponding configuration node to obtain the actual real-time flow of each path in the directed graph;

[0120] The deduction unit 114 is used to deduce the real-time traffic of each path in the directed graph using a preset traffic algorithm as the predicted real-time traffic of each path;

[0121] The analysis unit 112 is further used to perform overflow analysis according to the actual real-time flow of each path and the predicted real-time flow of each path to obtain the overflow analysis result of the area to be analyzed.

[0122] It can be seen from the above technical scheme that the present invention can construct a directed graph of the pipeline network of the area to be analyzed according to the monitoring nodes of the area to be analyzed, and perform node analysis on the directed graph to obtain configuration nodes, install flow monitoring equipment on the configuration nodes, and use the flow monitoring equipment to perform real-time flow monitoring on the corresponding configuration nodes to obtain the actual real-time flow of each path in the directed graph, so as to reasonably configure the optimal equipment installation nodes based on the directed graph to achieve effective monitoring of the regional flow; use a preset flow algorithm to deduce the real-time flow of each path in the directed graph as the predicted real-time flow of each path, and perform overflow analysis based on the actual real-time flow of each path and the predicted real-time flow of each path to obtain the overflow analysis result of the area to be analyzed, thereby achieving accurate overflow analysis of the regional flow.

[0123] like Figure 3 , which is a schematic diagram of the structure of a computer device of a preferred embodiment of the invention for implementing the overflow analysis method based on a directed graph.

[0124] The computer device 1 may include a memory 12, a processor 13 and a bus, and may also include a computer program stored in the memory 12 and executable on the processor 13, such as a directed graph-based overflow analysis program.

[0125] Those skilled in the art will appreciate that the schematic diagram is merely an example of the computer device 1 and does not constitute a limitation on the computer device 1. The computer device 1 may be a bus-type structure or a star-type structure. The computer device 1 may also include more or less other hardware or software than shown in the diagram, or a different arrangement of components. For example, the computer device 1 may also include input and output devices, network access devices, etc.

[0126] It should be noted that the computer device 1 is only an example, and other existing or future electronic products that are suitable for the present invention should also be included in the protection scope of the present invention and included here by reference.

[0127] The memory 12 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a mobile hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. In some embodiments, the memory 12 may be an internal storage unit of the computer device 1, such as a mobile hard disk of the computer device 1. In other embodiments, the memory 12 may also be an external storage device of the computer device 1, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the computer device 1. Further, the memory 12 may also include both an internal storage unit of the computer device 1 and an external storage device. The memory 12 may not only be used to store application software and various types of data installed in the computer device 1, such as the code of a directed graph-based overflow analysis program, but may also be used to temporarily store data that has been output or is to be output.

[0128] In some embodiments, the processor 13 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips. The processor 13 is the control core (Control Unit) of the computer device 1, and uses various interfaces and lines to connect various components of the entire computer device 1, and executes various functions and processes data of the computer device 1 by running or executing programs or modules stored in the memory 12 (for example, executing a directed graph-based overflow analysis program, etc.), and calling data stored in the memory 12.

[0129] The processor 13 executes the operating system of the computer device 1 and various installed applications. The processor 13 executes the applications to implement the steps in the above-mentioned embodiments of the overflow analysis method based on the directed graph, for example Figure 1 Steps shown.

[0130] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory 12 and executed by the processor 13 to complete the present invention. The one or more modules / units may be a series of computer-readable instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program in the computer device 1. For example, the computer program may be divided into an acquisition unit 110, a construction unit 111, an analysis unit 112, a monitoring unit 113, and a deduction unit 114.

[0131] The above-mentioned integrated unit implemented in the form of a software function module can be stored in a computer-readable storage medium. The above-mentioned software function module is stored in a storage medium, and includes a number of instructions for enabling a computer device (which can be a personal computer, a computer device, or a network device, etc.) or a processor to execute the part of the overflow analysis method based on a directed graph described in various embodiments of the present invention.

[0132] If the module / unit integrated in the computer device 1 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 present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware devices through a computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of each of the above-mentioned method embodiments can be implemented.

[0133] The computer program includes computer program code, which may be in source code form, object code form, 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 flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory, etc.

[0134] Furthermore, the computer-readable storage medium may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function, etc.; the data storage area may store data created according to the use of the blockchain node, etc.

[0135] The blockchain referred to in this invention is a new application mode of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, encryption algorithm, etc. Blockchain is essentially a decentralized database, a string of data blocks generated by cryptographic methods. Each data block contains a batch of network transaction information, which is used to verify the validity of its information (anti-counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, platform product service layer, and application service layer.

[0136] The bus can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 The bus is represented by only one straight line, but it does not mean that there is only one bus or one type of bus. The bus is configured to realize the connection and communication between the memory 12 and at least one processor 13, etc.

[0137] Although not shown, the computer device 1 may also include a power source (such as a battery) for supplying power to each component. Preferably, the power source may be logically connected to the at least one processor 13 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include any components such as one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, etc. The computer device 1 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0138] Furthermore, the computer device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is usually used to establish a communication connection between the computer device 1 and other computer devices.

[0139] Optionally, the computer device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touch device. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the computer device 1 and to display a visual user interface.

[0140] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0141] Figure 3 Only the computer device 1 having components 12-13 is shown, and it can be understood by those skilled in the art that Figure 3 The structure shown does not constitute a limitation on the computer device 1, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0142] Combination Figure 1 , the memory 12 in the computer device 1 stores a plurality of instructions to implement an overflow analysis method based on a directed graph, and the processor 13 can execute the plurality of instructions to implement:

[0143] In response to an overflow analysis instruction for a region to be analyzed, obtaining a monitoring node of the region to be analyzed;

[0144] Constructing a directed graph of the pipe network of the area to be analyzed according to the monitoring nodes;

[0145] Performing node analysis on the directed graph to obtain configuration nodes;

[0146] Installing a flow monitoring device on the configuration node, and using the flow monitoring device to perform real-time flow monitoring on the corresponding configuration node to obtain the actual real-time flow of each path in the directed graph;

[0147] Using a preset traffic algorithm to deduce the real-time traffic of each path in the directed graph as the predicted real-time traffic of each path;

[0148] An overflow analysis is performed based on the actual real-time flow of each path and the predicted real-time flow of each path to obtain an overflow analysis result of the area to be analyzed.

[0149] Specifically, the specific implementation method of the processor 13 for the above instructions can refer to Figure 1The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0150] It should be noted that the data involved in this case were all obtained legally.

[0151] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0152] The present invention can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present invention can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present invention can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0153] The modules described as separate components may or may not be physically separated, and the components shown as modules 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 modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0154] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0155] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0156] Therefore, no matter from which point of view, the embodiments should be regarded as illustrative and non-restrictive, and the scope of the present invention is limited by the appended claims rather than the above description, so it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any attached figure mark in the claims should not be regarded as limiting the claims involved.

[0157] In addition, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in the present invention can also be implemented by one unit or device through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any particular order.

[0158] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A directed graph-based overflow analysis method, characterized in that: The directed graph-based overflow analysis method includes: In response to an overflow analysis instruction for a region to be analyzed, obtaining a monitoring node of the region to be analyzed; Constructing a directed graph of the pipe network of the area to be analyzed according to the monitoring nodes; Performing node analysis on the directed graph to obtain configuration nodes; Installing a flow monitoring device on the configuration node, and using the flow monitoring device to perform real-time flow monitoring on the corresponding configuration node to obtain the actual real-time flow of each path in the directed graph; Using a preset traffic algorithm to deduce the real-time traffic of each path in the directed graph as the predicted real-time traffic of each path; An overflow analysis is performed based on the actual real-time flow of each path and the predicted real-time flow of each path to obtain an overflow analysis result of the area to be analyzed.

2. The directed graph-based overflow analysis method according to claim 1, characterized in that: The step of constructing a directed graph of the pipe network of the area to be analyzed according to the monitoring nodes comprises: Constructing the directed graph according to the pipe network structure and flow direction of the area to be analyzed; Wherein, each monitoring node in the directed graph is identified; Wherein, additional information is added to each graph node in the directed graph and a weight is added to each edge; The additional information includes a combination of one or more of the following information: location information, historical traffic data, maintenance status, and equipment capacity of each graph node; The weight of each edge is determined according to the flow capacity and pipe diameter of each edge.

3. The directed graph-based overflow analysis method according to claim 2, characterized in that: The performing node analysis on the directed graph to obtain the configuration node comprises: Obtain each cross node in the directed graph, and obtain the in-degree and out-degree of each cross node, calculate the sum of the in-degree of each cross node and the out-degree of each cross node to obtain the flow of each cross node, obtain a pre-configured flow threshold, and obtain the cross node whose calculated flow is greater than or equal to the flow threshold as a flow hub; Analyzing the directed graph based on a preset path analysis algorithm to obtain path intermediate points; wherein after removing the path intermediate points, the corresponding flow path is interrupted; The directed graph is analyzed based on a preset cut point algorithm to obtain vulnerable nodes; wherein after deleting the vulnerable nodes, the connectivity between other graph nodes in the directed graph except the vulnerable nodes is reduced; Performing cluster analysis on the traffic hubs, the path intermediate points and the vulnerable nodes to obtain each class; Get the centroid of each class as the configuration node.

4. The directed graph-based overflow analysis method according to claim 1, characterized in that: Before using the traffic monitoring device to perform real-time traffic monitoring on the corresponding configuration node, the method further includes: Obtaining historical monitoring parameters of the flow monitoring device; Calculating statistical values ​​of the historical monitoring parameters; The flow monitoring device is initialized according to the statistical value.

5. The directed graph-based overflow analysis method according to claim 1, characterized in that: The overflow analysis is performed according to the actual real-time flow of each path and the predicted real-time flow of each path to obtain the overflow analysis result of the area to be analyzed, including: Retrieving a pre-trained traffic anomaly detection model; wherein the traffic anomaly detection model is obtained by training based on a network model with classification function; Based on the traffic anomaly detection model, a comparison and analysis is performed on the actual real-time traffic of each path and the predicted real-time traffic of each path to obtain the overflow analysis result.

6. The directed graph-based overflow analysis method according to claim 2, characterized in that: After obtaining the overflow analysis result of the area to be analyzed, the method further includes: When the overflow analysis result shows that there is a flow abnormality, generating an abnormality report according to the overflow analysis result, and sending the abnormality report to a designated terminal device; or When the overflow analysis result shows that there is no flow abnormality, the real-time overflow analysis continues.

7. The directed graph-based overflow analysis method according to claim 1, characterized in that: The method further comprises: Configure the traffic warning line for each edge; When the flow of any edge in the directed graph reaches the corresponding flow warning line, an alarm is issued and the current flow data of the arbitrary edge is recorded.

8. An overflow analysis device based on directed graph, characterized in that: The directed graph-based overflow analysis device comprises: An acquisition unit, configured to acquire a monitoring node of the area to be analyzed in response to an overflow analysis instruction for the area to be analyzed; A construction unit, configured to construct a directed graph of the pipe network of the area to be analyzed according to the monitoring nodes; An analysis unit, used for performing node analysis on the directed graph to obtain configuration nodes; A monitoring unit, configured to install a flow monitoring device on the configuration node, and use the flow monitoring device to perform real-time flow monitoring on the corresponding configuration node to obtain the actual real-time flow of each path in the directed graph; A deduction unit, used for using a preset traffic algorithm to deduce the real-time traffic of each path in the directed graph as the predicted real-time traffic of each path; The analysis unit is also used to perform overflow analysis based on the actual real-time flow of each path and the predicted real-time flow of each path to obtain the overflow analysis result of the area to be analyzed.

9. A computer device, characterized in that: The computer device comprises: a memory storing at least one instruction; and A processor executes instructions stored in the memory to implement the directed graph-based overflow analysis method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one instruction, and the at least one instruction is executed by a processor in a computer device to implement the directed graph-based overflow analysis method as described in any one of claims 1 to 7.

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