Multi-source data early warning method and device for sponge city

Abstract

The invention relates to the technical field of information processing, in particular to a sponge city-oriented multi-source data early warning method and device, and the method comprises the steps: collecting simulation data of water seepage simulation early warning of a cloud platform and rainfall data of each type of city block; wherein the simulation data comprises urban overground layout data and urban underground layout data; determining the rainfall bearing limit of each city block according to the simulation data, the rainfall data and city management data of a multi-source early warning interface; according to the rainfall bearing limit of each city block, determining the single-day water seepage early warning times of each city block in accordance with the range rainfall permissible state; and according to the simulation data and the single-day water seepage early warning times of each city block, allocating associated simulation water seepage early warning to each city block. According to the invention, the processing time consumption for the multi-source data early warning of the sponge city can be saved, and the multi-source data early warning efficiency of the sponge city is improved.

Description

Technical Field

[0001] The present application relates to the field of information processing technology, and in particular to a multi-source data early warning method and device for sponge cities. Background Art

[0002] In the current sponge city construction process, in order to achieve the four functions of rainwater absorption, infiltration, purification and storage, improve the rainwater recycling rate in the city and reduce the probability of flood disasters. Various basic sponge facilities have been vigorously promoted in the process of sponge city construction, which has greatly improved the rainwater runoff reduction rate. However, in the actual rainfall process, the sponge facilities that absorb and utilize rainwater cannot effectively exert the ability of the facilities to absorb rainwater, which often leads to water seepage from time to time, bringing varying degrees of impact to residents.

[0003] Due to the differences in the performance of urban areas in multi-source sponge city data and the constant changes in the network environment, the time it takes for each urban area to send information to the city boundary is not uniform. The city boundary needs to wait for the slowest urban area to send information in a timely manner. Therefore, the speed of multi-source data warning in sponge cities is subject to the slowest urban area, resulting in a long processing time for multi-source data warning tasks in sponge cities.

[0004] It can be seen that how to improve the multi-source data early warning of sponge cities is a problem that technical personnel in this field need to solve. Summary of the invention

[0005] To achieve the above objectives, this application provides the following technical solutions: According to a first aspect of the present invention, the present invention claims protection for a multi-source data early warning method for sponge cities, comprising: Collecting simulation data of water seepage warning simulation on the cloud platform and rainfall data of each type of urban block; wherein the simulation data includes urban ground layout data and urban underground layout data; Determine the rainfall bearing limit of each urban block based on the simulation data, the rainfall data and the urban management data of the multi-source early warning interface; According to the rainfall bearing limit of each urban block, determine the number of single-day water seepage warnings for each urban block that meets the allowable rainfall status; Based on the simulation data and the number of water seepage warnings in each urban block on a single day, an associated simulated water seepage warning is allocated to each urban block.

[0006] Furthermore, the simulated data of water seepage warning simulated by the cloud platform and the rainfall data of each type of urban block include: Collecting simulation data of water seepage warning simulation on the cloud platform; wherein the simulation data includes the city model scale level value, complexity level, city block type in the multi-source warning interface, the total number of city blocks, and the total number of water seepage warnings in all city blocks in a single day; The simulated water seepage warning is transmitted to each type of urban block according to the simulated data, so as to obtain the predicted rainfall when the simulated water seepage warning is executed for each type of urban block under different single-day water seepage warning times.

[0007] Further, the transmitting of simulated water seepage warning to each type of urban block according to the simulated data to obtain predicted rainfall when each type of urban block performs simulated water seepage warning under different single-day water seepage warning times includes: One city block is selected from all city blocks of each city block type as the simulation scope; Transmitting different simulated water seepage warnings to the simulation range; wherein different simulated water seepage warnings are associated with different numbers of water seepage warnings per day; Execute different simulated rainfalls for water seepage warning according to the simulation range, and determine the predicted rainfall for the simulation range under different single-day water seepage warning times; Record the predicted rainfall associated with different daily water infiltration warning times for each urban block type.

[0008] Further, executing different simulated rainfalls for water seepage warning according to the simulation range to determine the predicted rainfall for the simulation range under different single-day water seepage warning times includes: Counting the simulated rainfall generated by each simulation of the candidate simulated water seepage warning executed within the simulation range; wherein the candidate simulated water seepage warning is any one of all the simulated water seepage warnings, and the candidate simulated water seepage warning is associated with the candidate single-day water seepage warning number; The average value of the simulated rainfall for a set number of times is used as the predicted rainfall in the simulation range under the candidate single-day water seepage warning number.

[0009] Furthermore, the method of using the average value of the simulated rainfall of the set number of times as the predicted rainfall in the simulation range under the candidate single-day water seepage warning number includes: The first N simulated rainfalls are eliminated from all simulated rainfalls generated by executing the candidate simulated water seepage warning in the simulation range based on real-time statistics, and the average value of the remaining simulated rainfalls that meet the set number of times is used as the predicted rainfall in the simulation range under the candidate single-day water seepage warning number.

[0010] Furthermore, the determining of the rainfall bearing limit of each urban block based on the simulation data, the rainfall data and the urban management data of the multi-source early warning interface includes: Collect the communication speed between each city block and the city boundary in the multi-source early warning interface; The rainfall carrying limit of each urban block is determined based on the urban model scale level value, complexity level, communication speed and predicted rainfall associated with the number of real-time daily water seepage warnings associated with each urban block.

[0011] Further, the communication speed includes traffic congestion level and urban drainage level; Accordingly, the rainfall carrying limit of each city block is determined according to the city model scale level value, complexity level, communication speed and predicted rainfall associated with the number of real-time daily water seepage warnings associated with each city block, including: According to the predicted rainfall when simulating water seepage warning under different single-day water seepage warning times for each type of urban block, a candidate predicted rainfall matching the urban block type and the real-time single-day water seepage warning times of the candidate urban block is determined; wherein the candidate urban block is any one of all urban blocks; The rainfall bearing limit of the candidate city block is determined based on the city model scale level value, complexity level, traffic congestion level, city drainage level and the candidate predicted rainfall associated with the candidate city block.

[0012] Furthermore, the determining of the rainfall bearing limit of the candidate city block according to the city model scale level value, complexity level, traffic congestion level, city drainage level and the candidate predicted rainfall associated with the candidate city block includes: Determining a first rainfall bearing limit according to the city model scale level value and the city drainage level; Determining a second rainfall bearing limit according to the complexity level and the traffic congestion level; The sum of the second rainfall bearing limit, the first rainfall bearing limit and the candidate predicted rainfall is used as the rainfall bearing limit of the candidate urban block.

[0013] Furthermore, the determining of the first rainfall bearing limit according to the city model scale level value and the city drainage level includes: The ratio of the city model scale level value to the city drainage level is used as the first rainfall bearing limit; Determining the second rainfall bearing limit according to the complexity level and the traffic congestion level includes: The ratio of the complexity level to the traffic congestion level is used as the second rainfall bearing limit.

[0014] According to a second aspect of the present invention, the present invention claims protection for a multi-source data early warning device for sponge cities, comprising a collection module, a rainfall bearing limit determination module, a water seepage early warning number determination module, and a distribution module; The collection module is used to collect simulation data of water seepage warning simulation on the cloud platform and rainfall data of each type of urban block; wherein the simulation data includes urban ground layout data and urban underground layout data; The rainfall bearing limit determination module is used to determine the rainfall bearing limit of each urban block based on the simulation data, the rainfall data and the urban management data of the multi-source warning interface; The water seepage warning number determination module is used to determine the number of water seepage warnings per day for each urban block that meets the range of rainfall allowable conditions according to the rainfall bearing limit of each urban block; The allocation module is used to allocate the associated simulated water seepage warning to each urban block based on the simulated data and the number of water seepage warnings in a single day in each urban block; The multi-source data early warning device for sponge cities is used to execute the multi-source data early warning method for sponge cities.

[0015] The present application relates to the field of information processing technology, and in particular to a multi-source data early warning method and device for sponge cities, which collects simulation data of water seepage early warning for a cloud platform and rainfall data for each type of urban block; wherein the simulation data includes urban ground layout data and urban underground layout data; based on the simulation data, the rainfall data and the urban management data of the multi-source early warning interface, the rainfall bearing limit of each urban block is determined; based on the rainfall bearing limit of each urban block, the number of water seepage early warnings per day that meet the range of rainfall allowed state of each urban block is determined; based on the simulation data and the number of water seepage early warnings per day of each urban block, the associated simulated water seepage early warning is allocated to each urban block. The present invention can save the time-consuming processing of multi-source data early warning for sponge cities and improve the efficiency of multi-source data early warning for sponge cities. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A workflow diagram of a multi-source data early warning method for sponge cities as claimed in the embodiments of the present application; Figure 2 A second working flow chart of a multi-source data early warning method for sponge cities claimed in the embodiment of the present application; Figure 3 A third working flow chart of a multi-source data early warning method for sponge cities claimed in an embodiment of the present application; Figure 4A fourth working flow chart of a multi-source data early warning method for sponge cities claimed in an embodiment of the present application; Figure 5 A structural module diagram of a multi-source data early warning device for sponge cities as claimed in an embodiment of the present application. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field without creative work based on the embodiments in the present application are within the scope of protection of this application.

[0018] The terms "first", "second" and "third" in this application are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined as "first", "second" and "third" can explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "multiple" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined. All directional indications (such as up, down, left, right, front, back...) in the embodiments of this application are only used to explain the relative position relationship, movement, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication also changes accordingly. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or modules is not limited to the listed steps or modules, but optionally also includes steps or modules that are not listed, or optionally also includes other steps or modules inherent to these processes, methods, products or devices.

[0019] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0020] Figure 1 A flowchart of a multi-source data early warning method for sponge cities provided by an embodiment of the present invention, the method comprising: S101: Collect simulation data of water seepage warning for the cloud platform and rainfall data for each type of urban block.

[0021] Among them, the simulation data may include data characterizing the prediction performance of the multi-source early warning interface.

[0022] In the embodiment of the present invention, each multi-source computing power is a city block. There can be multiple types of multi-source computing power. According to actual simulation requirements, when executing cloud platform simulation, multiple types of multi-source computing power can be called, and each type of multi-source computing power can have multiple.

[0023] The data characterizing the prediction performance of the multi-source early warning interface may include the urban model scale level value, complexity level, urban block type in the multi-source early warning interface, the total number of urban blocks, and the total number of single-day water seepage warnings for all urban blocks.

[0024] In practical applications, the symbol S It indicates the total number of water seepage warnings in a single day allocated by the cloud platform on all multi-source computing power. D W Indicates the scale level of the city model used by the cloud platform to simulate water seepage warning. D g Indicates the complexity level of the model used by the cloud platform to simulate water seepage warning.

[0025] The simulation data may include hardware configuration data and hardware network data. The hardware configuration data may include the multi-source computing power type (i.e., city block type) called by the cloud platform to simulate water seepage warning, and the total computing power (i.e., the total number of city blocks). Z Indicates the total number of city blocks. The hardware network data may include the address data of each multi-source computing power called by the cloud platform to simulate water seepage warning in the multi-source warning interface.

[0026] In order to facilitate the multi-source warning interface to distribute simulated water seepage warnings to different urban blocks, the simulation data may include all the data of the model to be simulated, such as the details of each layer in the model for simulating water seepage warning, the activation function of each layer, the loss function used in the simulation model, etc.

[0027] The rainfall data may include the predicted rainfall generated when the city block performs water seepage warning. Considering that the performance of the same type of city blocks is the same, for the same type of city blocks, only one city block needs to be selected from the same type of city blocks to perform simulated water seepage warning and collect its predicted rainfall.

[0028] In an embodiment of the present invention, after collecting simulation data of simulated water seepage warning on the cloud platform, the simulated water seepage warning can be transmitted to each type of urban block based on the simulation data to obtain the predicted rainfall when each type of urban block executes the simulated water seepage warning under different single-day water seepage warning times.

[0029] S102: Determine the rainfall bearing limit of each urban block based on the simulation data, rainfall data and urban management data of the multi-source warning interface.

[0030] The simulation data and rainfall data can reflect the prediction performance of urban blocks. In order to consider the impact of network resources when executing the cloud platform simulation water seepage warning, in an embodiment of the present invention, urban management data of a multi-source warning interface can be collected.

[0031] The city management data may include the communication speed between each city block and the city boundary in the multi-source early warning interface. In practical applications, some simulation tools may be used to collect the communication speed, for example, a network performance simulation tool may be used to simulate and collect the communication speed.

[0032] The rainfall carrying limit is used to characterize the rainfall generated by considering both the prediction performance of the city block and the network resources when performing water infiltration warning.

[0033] The rainfall data includes the predicted rainfall generated by simulating water seepage warning according to the predicted performance of the urban block. The simulation data includes the urban model scale level value and complexity level, which cooperates with the urban management data to determine the communication rainfall. In the embodiment of the present invention, the communication rainfall and the predicted rainfall of the urban block can be comprehensively considered to determine the rainfall bearing limit of the urban block.

[0034] S103: According to the rainfall bearing limit of each urban block, determine the number of water seepage warnings per day for each urban block that meets the permitted rainfall range.

[0035] The range rainfall allowable state may include the distribution of rainfall carrying limits of each city block when it reaches the controllable allowable state.

[0036] The number of daily water seepage warnings in urban blocks is different, and the predicted rainfall generated will also be different, thus affecting the rainfall bearing limit. Therefore, in an embodiment of the present invention, by correcting the number of daily water seepage warnings in urban blocks, the rainfall bearing limit of each urban block can be allowed.

[0037] If the rainfall bearing limit of each city block can be similar, then each city block can push timeliness to the city boundary almost at the same time. After the city boundary receives the timeliness of all city blocks, it will synchronize and update the parameters, and then return the updated parameters to each city block. After each city block receives the parameters, it will perform the next simulation iteration. In this process, the city boundary can receive the timeliness sent by all city blocks almost at the same time, which effectively improves the processing efficiency of the cloud platform simulation water seepage warning.

[0038] S104: Allocate associated simulated water seepage warnings to each urban block based on the simulation data and the number of water seepage warnings in each urban block on a single day.

[0039] The multi-source warning interface can reconstruct the cloud platform simulated water seepage warning based on the simulation data of the cloud platform simulated water seepage warning and the number of water seepage warnings in each urban block per day, and finally transmit it to each urban block in the multi-source warning interface.

[0040] It can be seen from the above technical solution that the simulation data of the cloud platform simulated water seepage warning and the rainfall data of each type of urban block are collected; the simulation data includes urban ground layout data and urban underground layout data. In order to improve the controllable and permissible effect of the cloud platform simulated water seepage warning, the network resources of the multi-source warning interface can be considered while considering the prediction capabilities of different urban blocks. Therefore, the rainfall bearing limit of each urban block can be determined based on the simulation data, rainfall data and urban management data of the multi-source warning interface; according to the rainfall bearing limit of each urban block, the number of single-day water seepage warnings in each urban block that meets the range of rainfall allowable status is determined; according to the simulation data and the number of single-day water seepage warnings in each urban block, the associated simulated water seepage warning is assigned to each urban block. The beneficial effect of the present invention is that when it is controllably permissible, not only the prediction performance of different urban blocks in the multi-source warning interface is considered, but also the network resources in the multi-source warning interface are considered, so that the controllable and permissible effect is better. Moreover, the process of achieving controllable allowance only requires correcting the number of water seepage warnings per day in each urban block, thereby ensuring that the controllable allowance is simple to implement, does not require complex algorithm programs, and does not affect the final convergence of the entire cloud platform's simulated water seepage warning and the performance of the simulated neural network.

[0041] Figure 2 A flowchart of a method for determining predicted rainfall for each type of urban block provided by an embodiment of the present invention, the method comprising: S201: Select one city block from all city blocks of each city block type as a simulation range.

[0042] There may be multiple city blocks of each type, and the performance of the same type of city blocks is the same. Therefore, when performing simulated water seepage warning to determine predicted rainfall, it is only necessary to simulate one city block of each type.

[0043] In practical applications, one city block may be selected from all city blocks of each city block type as the simulation range.

[0044] S202: Transmitting different simulated water seepage warnings to the simulation range.

[0045] Among them, the number of single-day water seepage warnings associated with different simulated water seepage warnings is different.

[0046] The number of water seepage warnings per day set in the simulation range is different, and the generated predicted rainfall will also be different. Therefore, in the embodiment of the present invention, different simulated water seepage warnings can be deployed, and each simulated water seepage warning has its associated number of water seepage warnings per day.

[0047] For example, assuming that the maximum number of water seepage warnings that a simulation range can support is n, then n simulated water seepage warnings can be set based on the number of water seepage warnings per day from 1 to n. The model in the simulated water seepage warning is exactly the same as the model of the original cloud platform simulated water seepage warning. The input data can be sampled from the original data set. The number of water seepage warnings per day associated with each simulated water seepage warning is different from the number of water seepage warnings initially set for the urban block. Instead, it is simulated based on the number of water seepage warnings per day from 1 to n, thereby obtaining the predicted rainfall associated with different numbers of water seepage warnings per day.

[0048] S203: Execute different simulated rainfalls for water seepage warning according to the simulation range to determine the predicted rainfall for the simulation range under different single-day water seepage warning times.

[0049] According to the conventional water seepage warning execution process, for each simulated water seepage warning, many iterative simulations need to be performed to determine its associated predicted rainfall. However, in actual applications, it is not necessary to fully execute all iterative simulations. It is only necessary to collect a set number of simulated rainfalls and take the average as the predicted rainfall to meet real-time simulation needs.

[0050] In a specific implementation, the simulated rainfall generated by each simulation of a candidate simulated water seepage warning executed within the simulation range can be counted; wherein, the candidate simulated water seepage warning is any simulated water seepage warning among all simulated water seepage warnings, and the candidate simulated water seepage warning is associated with the candidate single-day water seepage warning number; the average value of the set number of simulated rainfalls is used as the predicted rainfall within the simulation range under the candidate single-day water seepage warning number.

[0051] Taking into account the instability of the simulation results in the early stage, in order to ensure the accuracy of the predicted rainfall, the first N simulated rainfalls can be eliminated from all the simulated rainfalls generated by executing the candidate simulated water seepage warning in the simulation range of real-time statistics, and the average value of the remaining simulated rainfalls that meet the set number of times can be used as the predicted rainfall in the simulation range under the candidate single-day water seepage warning number.

[0052] In practical applications, N can be set to 10, and the set number can be set to 80. For example, the simulated rainfalls from the 10th to the 100th iterations of each simulated water seepage warning can be counted, and the simulated rainfalls can be averaged to obtain the predicted rainfall.

[0053] S204: Record the predicted rainfall associated with different single-day water seepage warning times for each urban block type.

[0054] In order to facilitate subsequent query calls, the predicted rainfall associated with different single-day water seepage warning times for each type of urban block can be recorded in a table. For example, the table can be divided into three columns, one column for representing the type of urban block, one column for representing the single-day water seepage warning times associated with the urban block, and another column for representing the predicted rainfall associated with the urban block. Each row of data contains the predicted rainfall associated with a type of urban block under the single-day water seepage warning times.

[0055] In the embodiment of the present invention, by setting different simulated water seepage warnings for each type of urban block, the predicted rainfall associated with the urban block under different single-day water seepage warning times can be obtained, which provides a basis for the subsequent determination of the rainfall bearing limit of the urban block. And after correcting the single-day water seepage warning times of the urban block, based on the recorded predicted rainfall, the predicted rainfall associated with the urban block under the real-time single-day water seepage warning times can be quickly obtained.

[0056] Figure 3 A flowchart of a method for determining the rainfall bearing limit of each urban block provided by an embodiment of the present invention, the method comprising: S301: Collect the communication speed between each city block and the city boundary in the multi-source early warning interface.

[0057] In the embodiment of the present invention, the prediction performance and network resources of the multi-source warning interface can be analyzed simultaneously, so as to determine the rainfall bearing limit of each urban block.

[0058] Network resources can include communication speeds between city blocks and city boundaries.

[0059] In practical applications, network simulation tools can be used to simulate the communication speed between each city block and the city boundary.

[0060] After collecting the communication speed from each city block to the city boundary, combined with the city model scale level value and complexity level associated with each city block, the communication rainfall of each city block can be determined. Combining the communication rainfall of each city block with the predicted rainfall, the rainfall carrying limit of each city block can be determined.

[0061] S302: Determine candidate predicted rainfall that matches the urban block type of the candidate urban block and the real-time daily water seepage warning number based on predicted rainfall when simulating water seepage warnings for each type of urban block under different daily water seepage warning numbers.

[0062] The method for determining the rainfall bearing limit of each urban block is similar. In the embodiment of the present invention, any one urban block among all urban blocks, namely, the candidate urban block, is taken as an example for description.

[0063] In an embodiment of the present invention, the predicted rainfall associated with different single-day water seepage warning numbers under each urban block type is recorded in the form of a table. Therefore, the table can be used to determine the candidate predicted rainfall that matches the urban block type of the candidate urban block and the real-time single-day water seepage warning number.

[0064] S303: Determine the rainfall bearing limit of the candidate city block according to the city model scale level value, complexity level, traffic congestion level, city drainage level and candidate predicted rainfall associated with the candidate city block.

[0065] The communication speed may include a traffic congestion level and an urban drainage level. The traffic congestion level indicates the speed from a city block to a city boundary, and the urban drainage level indicates the speed from a city boundary to a city block.

[0066] In an embodiment of the present invention, a first rainfall bearing limit can be determined based on the city model scale level value and the city drainage level; a second rainfall bearing limit can be determined based on the complexity level and the traffic congestion level; and the sum of the second rainfall bearing limit, the first rainfall bearing limit and the candidate predicted rainfall is used as the rainfall bearing limit of the candidate city block.

[0067] In practical applications, the ratio of the urban model scale level to the urban drainage level is used as the first rainfall bearing limit, and the ratio of the complexity level to the traffic congestion level is used as the second rainfall bearing limit.

[0068] According to the determination principle of rainfall bearing limit, the rainfall bearing limit formula can be constructed. By predicting according to the following formula, the rainfall bearing limit of urban blocks can be determined: ; in, Represents a city block X The rainfall bearing limit of It indicates the scale level of the city model used by the cloud platform to simulate water seepage warning. Represents city boundaries to city blocks X The urban drainage level, Represents a city block X The number of water seepage warnings in a single day is batch_size Time-dependent predicted rainfall, Indicates the complexity level of the model used to simulate water seepage warning on the cloud platform. Represents a city block X Traffic congestion level to the city boundary, represents the first rainfall bearing limit, Indicates the second rainfall bearing limit.

[0069] In practical applications, without controllable permission, the above-mentioned formula for predicting rainfall bearing limit can also be used to predict the predicted rainfall for simulated water seepage warning on the cloud platform at the city boundary.

[0070] In the embodiment of the present invention, in order not to affect the final convergence of the water seepage warning simulation of the entire cloud platform and the performance of the simulated neural network, the sum of the number of water seepage warnings per day for all city blocks can be kept unchanged. In the initial state, the initial number of water seepage warnings per day for each city block can be set according to the sum of the number of water seepage warnings per day for all city blocks and the total number of city blocks.

[0071] In practical applications, the initial single-day water seepage warning number for each urban block can be set based on an equal distribution method. For example, the ratio of the sum of the single-day water seepage warning numbers of all urban blocks to the total number of urban blocks can be used as the initial single-day water seepage warning number for each urban block.

[0072] In the embodiment of the present invention, the predicted rainfall of each city block can be used to characterize the prediction performance, and the second rainfall bearing limit and the first rainfall bearing limit can be used to characterize the network resources. The prediction performance and network resources of each city block are comprehensively considered to determine the rainfall bearing limit of each city block, thereby ensuring the accuracy of the rainfall bearing limit.

[0073] Figure 4 A flowchart of a method for determining the number of single-day water seepage warnings for each urban block that meets the range rainfall allowable state provided by an embodiment of the present invention, the method comprising: S401: Select the rainfall bearing limit peak value and rainfall bearing limit valley value of all urban blocks.

[0074] In the embodiment of the present invention, the number of water seepage warnings per day can be corrected by taking two urban blocks with the largest and smallest rainfall bearing limits as entry points.

[0075] When the urban blocks associated with the rainfall bearing limit peak value and the rainfall bearing limit valley value remain unchanged, it means that the rainfall bearing limits of each urban block have become the same. At this time, the number of single-day water seepage warnings associated with each urban block in real time can be used as the number of single-day water seepage warnings for each urban block that meets the allowable rainfall status within the range.

[0076] S402: Determine whether the first urban block associated with the peak value of the rainfall bearing limit and the second urban block associated with the valley value of the rainfall bearing limit are the same as the urban blocks selected historically.

[0077] Among them, the historical city blocks are empty in the initial state.

[0078] When the first city block associated with the peak value of the rainfall bearing limit and the second city block associated with the valley value of the rainfall bearing limit are the same as the city blocks selected historically, it means that the rainfall bearing limits of the city blocks have become the same, and S403 can be executed at this time.

[0079] When the first city block associated with the peak value of the rainfall bearing limit and the second city block associated with the valley value of the rainfall bearing limit are different from the city blocks selected historically, it means that the rainfall bearing limits of the city blocks have not yet converged, and S404 can be executed at this time.

[0080] S403: The number of water seepage warnings per day associated with each urban block in real time is used as the number of water seepage warnings per day in each urban block that meets the permitted rainfall status.

[0081] When the first urban block associated with the peak value of the rainfall bearing limit and the second urban block associated with the valley value of the rainfall bearing limit are the same as the urban blocks selected historically, it means that the number of single-day water seepage warnings associated with each urban block in real time has met the allowable state of range rainfall, and there is no need to correct the number of single-day water seepage warnings in the urban blocks. At this time, the number of single-day water seepage warnings associated with each urban block in real time can be used as the number of single-day water seepage warnings for each urban block that meets the allowable state of range rainfall.

[0082] S404: According to the set water seepage warning number correction granularity, the single-day water seepage warning number of the first city block associated with the peak value of the rainfall bearing limit and the single-day water seepage warning number of the second city block associated with the valley value of the rainfall bearing limit are corrected in sequence.

[0083] In practical applications, the granularity of each correction of the water seepage warning times can be pre-set. When the deviation between the peak value of the rainfall bearing limit and the valley value of the rainfall bearing limit is large, the granularity of the correction of the water seepage warning times can be set larger; when the deviation between the peak value of the rainfall bearing limit and the valley value of the rainfall bearing limit is small, the granularity of the correction of the water seepage warning times can be set smaller.

[0084] The granularity is corrected according to the set number of water seepage warnings, the number of water seepage warnings per day in the first urban block is reduced and the number of water seepage warnings per day in the second urban block is increased.

[0085] In order to achieve accurate correction of the number of water seepage warnings per day, the correction granularity of the number of water seepage warnings can be set to 1. Each time a correction is made, the number of water seepage warnings per day in the first city block can be reduced by one, and the number of water seepage warnings per day in the second city block can be increased by one.

[0086] S405: Re-determine the rainfall bearing limit of the first urban block and the rainfall bearing limit of the second urban block.

[0087] After correcting the single-day water seepage warning times of the first urban block and the second urban block, the predicted rainfall associated with the real-time single-day water seepage warning times of the first urban block and the predicted rainfall associated with the real-time single-day water seepage warning times of the second urban block can be determined based on the predicted rainfall associated with the different single-day water seepage warning times recorded for each urban block type.

[0088] After the predicted rainfall of the first city block and the second city block is determined, the rainfall bearing limit of the first city block and the rainfall bearing limit of the second city block can be re-determined according to the operation process of S303.

[0089] S406: If the rainfall bearing limit of the first city block and the rainfall bearing limit of the second city block meet the set rainfall deviation state, the granularity is corrected according to the set number of water seepage warnings, and the number of water seepage warnings per day of the first city block and the second city block is reversely corrected to redetermine the rainfall bearing limit of the first city block and the rainfall bearing limit of the second city block.

[0090] When the rainfall bearing limit of the first city block and the rainfall bearing limit of the second city block are re-determined, the process may return to S401 to re-select the rainfall bearing limit peak values ​​and rainfall bearing limit valley values ​​of all city blocks.

[0091] The rainfall deviation state can be set according to the relationship between the rainfall deviation of the rainfall bearing limit of the first city block and the second city block in real time and the historical rainfall deviation. The rainfall deviation can be the difference between the peak value of the rainfall bearing limit and the valley value of the rainfall bearing limit.

[0092] When the rainfall deviation becomes smaller and smaller, it means that correcting the number of daily water seepage warnings in the first urban block and the second urban block can achieve a better controllable and allowable effect. Once the rainfall deviation exceeds or is equal to the historical rainfall deviation, it means that the current round of correction can no longer achieve a controllable and allowable effect. At this time, a new round of correction is required, that is, returning to S401 to reselect the rainfall bearing limit peak value and rainfall bearing limit valley value of all urban blocks.

[0093] Therefore, in an embodiment of the present invention, each time the rainfall bearing limit of the first city block and the rainfall bearing limit of the second city block are re-determined, it can be determined whether the rainfall deviation between the rainfall bearing limit of the first city block and the rainfall bearing limit of the second city block is less than the historical rainfall deviation.

[0094] When the rainfall deviation between the rainfall bearing limit of the first city block and the rainfall bearing limit of the second city block is less than the historical rainfall deviation, it means that the number of daily water seepage warnings of the first city block and the second city block can continue to be corrected. At this time, the steps of reducing the number of daily water seepage warnings of the first city block and increasing the number of daily water seepage warnings of the second city block can be executed according to the set water seepage warning number correction granularity.

[0095] When the rainfall deviation between the rainfall bearing limit of the first city block and the rainfall bearing limit of the second city block exceeds or is equal to the historical rainfall deviation, it means that the correction of the real-time daily water seepage warning times of the first city block and the second city block can no longer achieve a better controllable allowable effect. At this time, the granularity of the water seepage warning times can be corrected according to the set water seepage warning times, the daily water seepage warning times of the first city block can be increased and the daily water seepage warning times of the second city block can be decreased, the rainfall bearing limits of the first city block and the second city block can be re-predicted, and then return to S401 to reselect the peak values ​​and valley values ​​of the rainfall bearing limits of all city blocks.

[0096] It should be noted that, in the embodiment of the present invention, in addition to determining whether to end the correction of the current round of single-day water seepage warning times according to the rainfall deviation, attention can also be paid to the corrected single-day water seepage warning times of the first city block and the second city block. After reducing the single-day water seepage warning times of the first city block and increasing the single-day water seepage warning times of the second city block according to the set water seepage warning times correction granularity, it can be further determined whether the single-day water seepage warning times of the first city block is zero or whether the single-day water seepage warning times of the second city block exceeds the threshold.

[0097] When the number of daily water seepage warnings in the first city block is zero or the number of daily water seepage warnings in the second city block exceeds the threshold, it means that the current round of correction can no longer achieve a better controllable and allowable effect. At this time, the granularity of the correction can be adjusted according to the set number of water seepage warnings, increasing the number of daily water seepage warnings in the first city block and reducing the number of daily water seepage warnings in the second city block.

[0098] Taking the correction granularity of the number of water seepage warnings as one as an example, in actual applications, if the number of water seepage warnings per day in the first city block is zero or the number of water seepage warnings per day in the second city block exceeds the threshold or the rainfall deviation between the rainfall bearing limit of the first city block and the rainfall bearing limit of the second city block exceeds or is equal to the historical rainfall deviation, the number of water seepage warnings per day in the first city block can be increased by one, and the number of water seepage warnings per day in the second city block can be reduced by one.

[0099] Assuming that the number of urban blocks is Z, the total number of water seepage warnings per day allocated by the cloud platform on all multi-source computing power is S. The number of water seepage warnings per day in urban blocks can be determined according to the following process.

[0100] Step 1: Initially given the batch_size =S / Z, and each city block batch_ size It can be recorded as b1, b2, ..., b Z .

[0101] Step 2: Determine the rainfall bearing limit of each city block, which can be expressed as .

[0102] Step 3: For the rainfall bearing limits of all urban blocks, find the peak value and valley value of the rainfall bearing limit, assuming that T X,p and T X,q , where the subscripts p and q represent the numbers of the city blocks. City block p is the first city block introduced above, and city block q is the second city block introduced above.

[0103] Step 4: Record the city block p and city block q selected this time. If they are the same as the city block p and city block q that entered this step in the past, go to step 6; otherwise, go to step 5.

[0104] Step 5: Prediction , let b p =b p -1, b q =b q +1. Among them, b p represents the number of water seepage warnings associated with urban block p in a single day, b q represents the number of water seepage warnings associated with urban block q in a single day. p =b p -1 means that the number of water seepage warnings per day in urban block p is reduced by 1 as the new number of water seepage warnings per day. q =b q +1 means adding 1 to the daily water seepage warning number of city block q as the new daily water seepage warning number. After correcting the daily water seepage warning number of city blocks p and q, the rainfall bearing limit of city block p can be re-determined. T X,p and the rainfall bearing limit of urban block q T X,q , the difference between the rainfall bearing limits of urban block p and urban block q at this time is recorded as .

[0105] if or b p =0 or b q If the threshold value of its association is exceeded, then another p =b p +1, b q =b q -1, after correcting the number of daily water seepage warnings for urban blocks p and q, the rainfall bearing limit of urban block p is re-determined T X,p and the rainfall bearing limit of urban block q T X,q , and return to step 3.

[0106] Otherwise, if , repeat step 5.

[0107] Step 6: b1, b2, ..., b modified by the algorithm Z , which is the result of the algorithm output, indicating the associated batch_size .

[0108] From the above steps, it can be seen that the algorithm will not change the batch_size The sum S, therefore, will not affect the final performance of the neural network simulated by the final cloud platform.

[0109] In one iteration of cloud platform simulation, the time spent by each city block includes pulling the first rainfall carrying limit associated with the parameter, the predicted rainfall associated with the local simulation, and pushing the second rainfall carrying limit associated with timeliness. When the city boundary receives the timeliness of all city blocks, it will synchronize the parameters and then return the updated parameters to each city block. Each city block can only proceed to the next simulation iteration after receiving the parameters.

[0110] In this process, the city boundary can receive the timely transmission of all city blocks almost at the same time, which effectively reduces the processing rainfall of the cloud platform to simulate the water seepage warning.

[0111] Figure 5 A schematic diagram of the structure of a multi-source data early warning device for sponge cities provided by an embodiment of the present invention, comprising a collection module 51, a rainfall bearing limit determination module 52, a water seepage early warning number determination module 53, and a distribution module 54; The collection module 51 is used to collect the simulation data of water seepage warning simulation on the cloud platform and the rainfall data of each type of urban block; wherein the simulation data includes the urban ground layout data and the urban underground layout data; A rainfall bearing limit determination module 52 is used to determine the rainfall bearing limit of each urban block based on simulation data, rainfall data and urban management data of a multi-source warning interface; The water seepage warning number determination module 53 is used to determine the number of water seepage warnings per day for each urban block that meets the range of rainfall allowable conditions according to the rainfall bearing limit of each urban block; The allocation module 54 is used to allocate the associated simulated water seepage warning to each urban block based on the simulation data and the number of water seepage warnings in a single day in each urban block.

[0112] In some embodiments, the collection module is used to collect simulation data of water seepage warning simulation on the cloud platform; wherein the simulation data includes the city model scale level value, complexity level, city block type in the multi-source warning interface, the total number of city blocks, and the total number of water seepage warnings in a single day for all city blocks; The simulated water seepage warning is transmitted to each type of urban block according to the simulated data, so as to obtain the predicted rainfall when the simulated water seepage warning is executed for each type of urban block under different single-day water seepage warning times.

[0113] In some embodiments, the acquisition module includes a selection submodule, a transmission submodule, a predicted rainfall determination submodule, and a recording submodule; A selection submodule is used to select one city block from all city blocks of each city block type as a simulation range; A transmission submodule is used to transmit different simulated water seepage warnings to the simulation range; wherein different simulated water seepage warnings are associated with different single-day water seepage warning times; The predicted rainfall determination submodule is used to perform different simulated rainfalls for water seepage warning according to the simulation range, and determine the predicted rainfall for the simulation range under different single-day water seepage warning times; The recording submodule is used to record the predicted rainfall associated with different daily water seepage warning times for each urban block type.

[0114] In some embodiments, the predicted rainfall determination submodule is used to count the simulated rainfall generated by each simulation of the candidate simulated water seepage warning executed within the simulation range; wherein the candidate simulated water seepage warning is any one of all the simulated water seepage warnings, and the candidate simulated water seepage warning is associated with the candidate single-day water seepage warning number; The average value of the simulated rainfall for the set number of times is taken as the predicted rainfall in the simulation range under the candidate single-day water seepage warning number.

[0115] In some embodiments, the predicted rainfall determination submodule is used to eliminate the first N simulated rainfalls from all simulated rainfalls generated by executing candidate simulated water seepage warnings within the real-time statistical simulation range, and take the average value of the remaining simulated rainfalls that meet the set number of times as the predicted rainfall within the simulation range under the candidate single-day water seepage warning number.

[0116] In some embodiments, the rainfall bearing limit determination module includes a velocity acquisition submodule and a rainfall determination submodule; The speed collection submodule is used to collect the communication speed between each city block and the city boundary in the multi-source warning interface; The rainfall determination submodule is used to determine the rainfall carrying limit of each urban block based on the predicted rainfall associated with the urban model scale level value, complexity level, communication speed and real-time daily water seepage warning number associated with each urban block.

[0117] In some embodiments, the communication speed includes a traffic congestion level and an urban drainage level; Correspondingly, the rainfall determination submodule is used to perform the predicted rainfall when simulating water seepage warning under different single-day water seepage warning times for each type of urban block, and determine the candidate predicted rainfall that matches the urban block type of the candidate urban block and the real-time single-day water seepage warning times; wherein the candidate urban block is any urban block among all urban blocks; The rainfall carrying limit of the candidate urban blocks is determined based on the urban model scale level value, complexity level, traffic congestion level, urban drainage level and candidate predicted rainfall associated with the candidate urban blocks.

[0118] In some embodiments, the rainfall determination submodule is used to determine a first rainfall bearing limit based on the city model scale level value and the city drainage level; According to the complexity level and traffic congestion level, the second rainfall bearing limit is determined; The sum of the second rainfall bearing limit, the first rainfall bearing limit and the candidate predicted rainfall is taken as the rainfall bearing limit of the candidate urban block.

[0119] In some embodiments, the rainfall determination submodule is used to use the ratio of the city model scale level value to the city drainage level as the first rainfall bearing limit.

[0120] In some embodiments, the rainfall determination submodule is configured to use a ratio of the complexity level to the traffic congestion level as the second rainfall bearing limit.

[0121] In some embodiments, for setting the number of water seepage warnings per day for each city block, the device includes a setting module; The setting module is used to set the initial single-day water seepage warning number for each urban block according to the sum of the single-day water seepage warning numbers of all urban blocks and the total number of urban blocks.

[0122] In some embodiments, the setting module is used to use the ratio of the sum of the single-day water seepage warning times of all urban blocks to the total number of urban blocks as the initial single-day water seepage warning times of each urban block.

[0123] In some embodiments, the water seepage warning number determination module includes a selection submodule, a first correction submodule, a second correction submodule, and an acting submodule; A selection submodule is used to select the rainfall bearing limit peak value and rainfall bearing limit valley value of all urban blocks; The first correction submodule is used to correct the single-day water seepage warning number of the first city block associated with the peak value of the rainfall bearing limit and the single-day water seepage warning number of the second city block associated with the valley value of the rainfall bearing limit according to the set water seepage warning number correction granularity, and trigger the rainfall determination submodule to re-determine the rainfall bearing limit of the first city block and the rainfall bearing limit of the second city block; The second correction submodule is used to correct the single-day water seepage warning times of the first city block and the second city block according to the set water seepage warning times correction granularity when the rainfall bearing limit of the first city block and the rainfall bearing limit of the second city block meet the set rainfall deviation state, re-determine the rainfall bearing limit of the first city block and the rainfall bearing limit of the second city block, and return to the step of selecting the peak value and valley value of the rainfall bearing limit of all city blocks; As a submodule, it is used to take the number of single-day water seepage warnings associated with each urban block in real time as the number of single-day water seepage warnings for each urban block that meets the allowable rainfall status until the urban blocks associated with the rainfall bearing limit peak value and the rainfall bearing limit valley value remain unchanged.

[0124] In some embodiments, a range determination module is also included; A range judgment module is used to judge whether the first city block associated with the peak value of the rainfall bearing limit and the second city block associated with the valley value of the rainfall bearing limit are the same as the city blocks selected historically; wherein, in the initial state, the historical city blocks are empty; When the first city block associated with the peak value of the rainfall bearing limit and the second city block associated with the valley value of the rainfall bearing limit are the same as the city blocks selected in history, the submodule is triggered to use the number of single-day water seepage warnings associated with each city block in real time as the number of single-day water seepage warnings for each city block that meets the range of rainfall allowable status; When the first urban block associated with the peak value of the rainfall bearing limit and the second urban block associated with the valley value of the rainfall bearing limit are different from the urban blocks selected historically, the first correction submodule is triggered to execute the steps of correcting the number of water seepage warnings per day of the first urban block associated with the peak value of the rainfall bearing limit and the number of water seepage warnings per day of the second urban block associated with the valley value of the rainfall bearing limit in sequence according to the set water seepage warning correction granularity.

[0125] In some embodiments, the first correction submodule is used to correct the granularity according to the set water seepage warning number, reduce the number of water seepage warnings per day in the first city block and increase the number of water seepage warnings per day in the second city block.

[0126] In some embodiments, the second correction submodule is used to determine whether the rainfall deviation between the rainfall bearing limit of the first city block and the rainfall bearing limit of the second city block is less than the historical rainfall deviation each time the rainfall bearing limit of the first city block and the rainfall bearing limit of the second city block are re-determined; When the rainfall deviation between the rainfall bearing limit of the first city block and the rainfall bearing limit of the second city block is less than the historical rainfall deviation, the step of reducing the number of single-day water seepage warnings in the first city block and increasing the number of single-day water seepage warnings in the second city block is performed according to the set water seepage warning number correction granularity; When the rainfall deviation between the rainfall bearing limit of the first city block and the rainfall bearing limit of the second city block exceeds or is equal to the historical rainfall deviation, the granularity of the water seepage warning number correction is adjusted according to the set number of water seepage warnings, increasing the number of single-day water seepage warnings in the first city block and reducing the number of single-day water seepage warnings in the second city block.

[0127] In some embodiments, after the water seepage warning number correction granularity is set according to which the water seepage warning number of the first city block is reduced and the water seepage warning number of the second city block is increased, a water seepage warning number judgment module is further included; A water seepage warning number judgment module is used to judge whether the number of water seepage warnings in a first city block on a single day is zero or whether the number of water seepage warnings in a second city block on a single day exceeds a threshold; When the number of water seepage warnings per day in the first city block is zero or the number of water seepage warnings per day in the second city block exceeds a threshold, the second correction submodule is triggered to correct the granularity of the water seepage warning number according to the set water seepage warning number, increase the number of water seepage warnings per day in the first city block and decrease the number of water seepage warnings per day in the second city block.

[0128] In some embodiments, the first correction submodule is used to reduce the number of water seepage warnings in a first city block by one, and increase the number of water seepage warnings in a second city block by one.

[0129] In some embodiments, the second correction submodule is used to increase the number of water seepage warnings in a first city block by one, and decrease the number of water seepage warnings in a second city block by one.

[0130] In the several embodiments provided in the present application, 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 schematic. For example, the division of modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules 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 interfaces, devices or modules, which can be electrical, mechanical or other forms.

[0131] In addition, each functional module in each embodiment of the present application can be integrated into a processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. The above is only an implementation method of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the specification and drawings of this application, or directly or indirectly used in other related technical fields, are also included in the patent protection scope of the present application.

[0132] The specific implementation methods of the invention are described in detail above, but they are only examples, and the present application is not limited to the specific implementation methods described above. For those skilled in the art, any equivalent modification or substitution of the invention is also within the scope of the present application, and therefore, the equalization, modification, and improvement made without departing from the spirit and principle of the present application should be included in the scope of the present application.

Claims

1. A multi-source data early warning method for sponge cities, characterized in that: include: Collecting simulation data of water seepage warning simulation on the cloud platform and rainfall data of each type of urban block; wherein the simulation data includes urban ground layout data and urban underground layout data; Determine the rainfall bearing limit of each urban block based on the simulation data, the rainfall data and the urban management data of the multi-source early warning interface; According to the rainfall bearing limit of each urban block, determine the number of single-day water seepage warnings for each urban block that meets the allowable rainfall status; Based on the simulation data and the number of water seepage warnings in each urban block on a single day, an associated simulated water seepage warning is allocated to each urban block.

2. The multi-source data early warning method for sponge cities according to claim 1, characterized in that: The simulated data of water seepage warning simulation collected by the cloud platform and the rainfall data of each type of urban block include: Collecting simulation data of water seepage warning simulation on the cloud platform; wherein the simulation data includes the city model scale level value, complexity level, city block type in the multi-source warning interface, the total number of city blocks, and the total number of water seepage warnings in all city blocks in a single day; The simulated water seepage warning is transmitted to each type of urban block according to the simulated data, so as to obtain the predicted rainfall when the simulated water seepage warning is executed for each type of urban block under different single-day water seepage warning times.

3. The multi-source data early warning method for sponge cities according to claim 2, characterized in that: The transmitting of the simulated water seepage warning to each type of urban block according to the simulated data to obtain the predicted rainfall when each type of urban block performs the simulated water seepage warning under different single-day water seepage warning times includes: One city block is selected from all city blocks of each city block type as the simulation scope; Transmitting different simulated water seepage warnings to the simulation range; wherein different simulated water seepage warnings are associated with different numbers of water seepage warnings per day; Execute different simulated rainfalls for water seepage warning according to the simulation range, and determine the predicted rainfall for the simulation range under different single-day water seepage warning times; Record the predicted rainfall associated with different daily water infiltration warning times for each urban block type.

4. The multi-source data early warning method for sponge cities as claimed in claim 3 is characterized in that: The step of executing different simulated water seepage warning rainfalls according to the simulation range to determine the predicted rainfall for the simulation range under different single-day water seepage warning times includes: Counting the simulated rainfall generated by each simulation of the candidate simulated water seepage warning executed within the simulation range; wherein the candidate simulated water seepage warning is any one of all the simulated water seepage warnings, and the candidate simulated water seepage warning is associated with the candidate single-day water seepage warning number; The average value of the simulated rainfall for a set number of times is used as the predicted rainfall in the simulation range under the candidate single-day water seepage warning number.

5. The multi-source data early warning method for sponge cities as claimed in claim 4, characterized in that: The method of taking the average value of the simulated rainfall of the set number of times as the predicted rainfall in the simulation range under the candidate single-day water seepage warning number includes: The first N simulated rainfalls are eliminated from all simulated rainfalls generated by executing the candidate simulated water seepage warning in the simulation range based on real-time statistics, and the average value of the remaining simulated rainfalls that meet the set number of times is used as the predicted rainfall in the simulation range under the candidate single-day water seepage warning number.

6. The multi-source data early warning method for sponge cities according to claim 2, characterized in that: Determining the rainfall bearing limit of each urban block based on the simulation data, the rainfall data and the urban management data of the multi-source early warning interface includes: Collect the communication speed between each city block and the city boundary in the multi-source early warning interface; The rainfall carrying limit of each urban block is determined based on the urban model scale level value, complexity level, communication speed and predicted rainfall associated with the number of real-time daily water seepage warnings associated with each urban block.

7. The multi-source data early warning method for sponge cities according to claim 6, characterized in that: The communication speed includes traffic congestion level and urban drainage level; Accordingly, the rainfall carrying limit of each city block is determined according to the city model scale level value, complexity level, communication speed and predicted rainfall associated with the number of real-time daily water seepage warnings associated with each city block, including: According to the predicted rainfall when simulating water seepage warning under different single-day water seepage warning times for each type of urban block, a candidate predicted rainfall matching the urban block type and the real-time single-day water seepage warning times of the candidate urban block is determined; wherein the candidate urban block is any one of all urban blocks; The rainfall bearing limit of the candidate city block is determined based on the city model scale level value, complexity level, traffic congestion level, city drainage level and the candidate predicted rainfall associated with the candidate city block.

8. The multi-source data early warning method for sponge cities according to claim 7, characterized in that: Determining the rainfall bearing limit of the candidate city block according to the city model scale level value, complexity level, traffic congestion level, city drainage level and the candidate predicted rainfall associated with the candidate city block includes: Determining a first rainfall bearing limit according to the city model scale level value and the city drainage level; Determining a second rainfall bearing limit according to the complexity level and the traffic congestion level; The sum of the second rainfall bearing limit, the first rainfall bearing limit and the candidate predicted rainfall is used as the rainfall bearing limit of the candidate urban block.

9. The multi-source data early warning method for sponge cities as claimed in claim 8, characterized in that: Determining the first rainfall bearing limit according to the city model scale level value and the city drainage level includes: The ratio of the city model scale level value to the city drainage level is used as the first rainfall bearing limit; Determining the second rainfall bearing limit according to the complexity level and the traffic congestion level includes: The ratio of the complexity level to the traffic congestion level is used as the second rainfall bearing limit.

10. A multi-source data early warning device for sponge cities, characterized in that: It includes a collection module, a rainfall bearing limit determination module, a water seepage warning times determination module, and a distribution module; The collection module is used to collect simulation data of water seepage warning simulation on the cloud platform and rainfall data of each type of urban block; wherein the simulation data includes urban ground layout data and urban underground layout data; The rainfall bearing limit determination module is used to determine the rainfall bearing limit of each urban block based on the simulation data, the rainfall data and the urban management data of the multi-source warning interface; The water seepage warning number determination module is used to determine the number of water seepage warnings per day for each urban block that meets the range of rainfall allowable conditions according to the rainfall bearing limit of each urban block; The allocation module is used to allocate the associated simulated water seepage warning to each urban block based on the simulated data and the number of water seepage warnings in a single day in each urban block; The multi-source data early warning device for sponge cities is used to execute the multi-source data early warning method for sponge cities as described in any one of claims 1-9.

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