An ecological whole-process initial rainwater pollution control method

Abstract

This invention relates to the field of pollution control technology and discloses an ecological method for controlling initial rainwater pollution throughout its entire process. The method includes: identifying a target control area and pollution control system; identifying multiple experimental simulation area groups; obtaining multiple matching nodes based on a set of control parameters; constructing a target monitoring environment based on the matching nodes; obtaining target monitoring parameters based on the target monitoring environment; obtaining reference decontamination assessment values ​​using the target monitoring environment and a water quality testing unit; identifying a target decontamination fitting parameter database based on the reference decontamination assessment values ​​and the target monitoring parameters; obtaining target area monitoring parameters and reference monitoring parameters for the target control area; and retrieving target control parameters from the target decontamination fitting parameter database based on the target area monitoring parameters and reference monitoring parameters, thereby achieving initial rainwater pollution control in the target control area. The main objective of this invention is to improve the accuracy of initial rainwater pollution control.

Description

Technical Field

[0001] This invention relates to an ecological method for controlling initial rainwater pollution throughout the entire process, belonging to the field of pollution control technology. Background Technology

[0002] With the acceleration of urbanization, urban stormwater pollution has become increasingly serious. Initial stormwater runoff often carries a large amount of pollutants, which can lead to problems such as eutrophication of water bodies. Correspondingly, improving the accuracy of pollution control for initial stormwater runoff has become an urgent issue to be addressed.

[0003] Currently, rainwater pollution control relies heavily on experience in deploying initial rainwater pollution control equipment and combining this experience with the actual control of initial rainwater pollution.

[0004] While the above methods can achieve pollution control of initial rainwater, they do not take into account the characteristics of pollutants in the area to be controlled and the characteristics of pollutants that different facilities can handle. Therefore, using empirical methods to lay out initial rainwater pollution control equipment and treat initial rainwater pollution may lead to inaccurate pollution control of initial rainwater. Summary of the Invention

[0005] This invention provides an ecological method, apparatus, and computer-readable storage medium for the whole-process control of initial rainwater pollution, the main purpose of which is to improve the accuracy of pollution control of initial rainwater.

[0006] To achieve the above objectives, the present invention provides an ecological method for controlling initial stormwater pollution throughout the entire process, comprising:

[0007] Receive control instructions and confirm the pollution control environment based on the control instructions. The pollution control environment includes the target control area and the pollution control system. The pollution control system includes: area confirmation unit, parameter confirmation unit and water quality detection unit.

[0008] Multiple experimental simulation region groups were identified based on the region identification unit, wherein each experimental simulation region group includes multiple experimental simulation regions;

[0009] The system confirms receipt of the parameter confirmation instruction from the parameter confirmation unit, parses the parameter confirmation instruction, and obtains a set of control parameters, wherein the set of control parameters includes multiple control parameter ranges. Based on the set of control parameters, multiple first fitting parameter groups are obtained. In a combined manner, multiple matching nodes are obtained using multiple first fitting parameter groups and multiple experimental simulation region groups. Each matching node includes one first fitting parameter group and one experimental simulation region group.

[0010] For each of the multiple matching nodes, perform the following operation:

[0011] A target monitoring environment is constructed based on the matching nodes;

[0012] Target monitoring parameters are obtained based on the target monitoring environment, including reference rainfall time, reference rainfall pattern and reference rainfall intensity. Reference decontamination assessment values ​​are obtained using the target monitoring environment and water quality detection unit.

[0013] Based on the reference decontamination assessment values ​​and target monitoring parameters, a target decontamination fitting parameter database was identified. The target decontamination fitting parameter database includes multiple target decontamination fitting parameter data, and the target decontamination fitting parameter data includes reference area monitoring parameters, target fitting parameter groups, and target monitoring parameters.

[0014] The target area monitoring parameters and reference monitoring parameters of the target control area are obtained. Based on the target area monitoring parameters and reference monitoring parameters, the target control parameters are retrieved from the target decontamination fitting parameter database to achieve the initial rainwater pollution control of the target control area.

[0015] Optionally, the region confirmation unit identifies multiple experimental simulation region groups, including:

[0016] Upon receiving the region confirmation instruction from the region confirmation unit, the region confirmation instruction is parsed to obtain multiple initial proposed regions. For each of the multiple initial proposed regions, the following operations are performed:

[0017] The initially planned region is divided using a preset region division window to obtain multiple initial division regions. The following operations are performed on each of the multiple initial division regions:

[0018] The geometric center of the initial division region is identified, the reference coordinates of the geometric center are obtained, and the initial division region is marked using the reference coordinates to obtain marked division regions. The marked division regions are summarized to obtain multiple marked division regions, and each marked division region corresponds one-to-one with the initial division region.

[0019] The number of initial division regions in multiple initial division regions is counted to obtain the initial division number. The product of the preset extraction density ratio and the initial division number is calculated to obtain the region extraction number. Based on the region extraction number and the pre-constructed uniform sampling algorithm, multiple target detection regions are identified in multiple labeled division regions.

[0020] For each of the multiple target detection regions, perform the following operation:

[0021] The concentration groups of pollutants to be detected are obtained based on the target detection area. The concentration groups of pollutants to be detected include the concentrations of multiple pollutants with their names.

[0022] The detected pollutant concentration groups are summarized to obtain a set of detected pollutant concentration groups, and multiple experimental simulation region groups are obtained based on the set of detected pollutant concentration groups.

[0023] Optionally, obtaining multiple experimental simulation region groups based on the detected pollutant concentration set includes:

[0024] The pollutant concentrations in each concentration set are summarized using the pollutant name, resulting in multiple analytical pollutant concentration sets. For each of these sets, the following operations are performed:

[0025] Multiple target prediction regions were identified across multiple labeled regions. The following operations were performed on each of these target prediction regions:

[0026] Based on the target prediction region, the pre-constructed pollution prediction formula and the analysis of pollutant concentration set, the predicted pollutant concentration is calculated, the predicted pollutant concentration is summarized to obtain the predicted pollutant concentration group, and the target prediction region is identified using the predicted pollutant concentration group to obtain the identified prediction region.

[0027] The target detection area is marked using the pollutant concentration group to obtain the marked detection area;

[0028] The target partitioning region set is obtained by summing the detected region and the predicted region. The target partitioning region set includes multiple target partitioning regions, and the target partitioning regions are the detected region or the predicted region.

[0029] A monitoring cluster dataset is extracted from the target segmented regions. This dataset contains multiple monitoring clusters, each corresponding one-to-one with a target segmented region. The monitoring cluster data is shown below:

[0030] C = (z, N1, N2, ..., N) H ,…,N M )

[0031] Where C represents the monitoring clustering data, z represents the reference coordinates corresponding to the target partitioned region, and N1, N2, N... H These represent the first, second, and Hth predicted pollutant concentrations in the predicted pollutant concentration group or the first, second, and Hth pollutant concentrations in the detected pollutant concentration group corresponding to the target area, respectively. M indicates that there are a total of M predicted pollutant concentrations or pollutant concentrations in the predicted pollutant concentration group or the detected pollutant concentration group.

[0032] Multiple experimental simulation region groups were obtained based on the monitoring clustering dataset and the target partitioning region set.

[0033] Optionally, the pollution prediction relationship is as follows:

[0034]

[0035] Among them, J i J represents the concentration of the i-th pollutant in the analysis of pollutant concentration concentrations. max d(Y0, Y0) represents the preset reference pollutant concentration, which is related to the name of the pollutant corresponding to the i-th pollutant concentration; t represents the preset proportion threshold; p0 represents the preset weight value; {} represents rounding up; Y0 represents the predicted pollutant concentration corresponding to the target prediction area; n represents the total number of pollutant concentrations in the analyzed pollutant concentration set; d(Y0, Y0) = 1. i ) represents the Euclidean distance between the reference coordinates corresponding to the target prediction area and the reference coordinates corresponding to the target detection area for the i-th pollutant concentration.

[0036] Optionally, obtaining multiple experimental simulation region groups based on the monitoring clustering dataset and the target partitioning region set includes:

[0037] Using the pollutant names, multiple sets of analytical pollutant concentrations are extracted from the monitoring cluster dataset. Each set of analytical pollutant concentrations corresponds one-to-one with a pollutant name, and each set includes multiple analytical pollutant concentrations. The analytical pollutant concentrations are either predicted pollutant concentrations or pollutant concentrations, and each analytical pollutant concentration corresponds one-to-one with an initially defined region.

[0038] For each of the multiple analytical contaminant concentration sets, perform the following operation:

[0039] Based on the pollutant name, a pollution control threshold is obtained. Using the pollution control threshold, a pollution control concentration set is extracted from the analysis of the pollution concentration set. The pollution control concentration set includes multiple pollution control concentrations, and the pollution control concentration is greater than or equal to the pollution control threshold.

[0040] The number of pollution concentrations treated in a concentrated manner is statistically analyzed to obtain the number of treatment areas. The ratio of the number of treatment areas to the initial number of divisions is calculated to obtain the treatment area ratio.

[0041] If the proportion of the treated area is greater than or equal to the preset treatment proportion threshold, the monitoring cluster dataset is updated using the treated pollution concentration set to obtain the updated monitoring cluster dataset.

[0042] Otherwise, the analytical pollution concentrations corresponding to the analytical pollution concentration set are removed from the monitoring cluster dataset to obtain the updated monitoring cluster dataset;

[0043] Based on the updated monitoring clustering dataset and the target partitioning region set, multiple experimental simulation region groups were obtained.

[0044] Optionally, obtaining multiple experimental simulation region groups based on the updated monitoring clustering dataset and the target partitioned region set includes:

[0045] The update monitoring clustering dataset is clustered using a pre-built clustering algorithm to obtain multiple grouped datasets. The following operations are performed on each of the multiple grouped datasets:

[0046] Using the grouped dataset, the grouped partitioning region set is identified within the target partitioning region set;

[0047] Multiple target fitting regions are obtained based on the preset treatment area and the grouped region set, wherein the area corresponding to the target fitting region is the treatment area;

[0048] Based on the preset simulated classification values, multiple experimental simulation region groups are extracted from multiple target fitting regions. Each experimental simulation region group includes multiple experimental simulation regions, and the number of experimental simulation regions contained in each experimental simulation region group is the simulated classification value.

[0049] Optionally, obtaining multiple first fitting parameter sets based on the control parameter set includes:

[0050] For each range of control parameters in the control parameter set, perform the following operation:

[0051] Using preset sampling values, uniform sampling is performed within the range of control parameters to obtain a sampling control parameter group, wherein the sampling control parameter group includes multiple sampling control parameters, and the number corresponding to the sampling control parameters is the sampling value;

[0052] The sampling control parameter sets are summarized to obtain a sampling control parameter set. Multiple first fitting parameter sets are obtained by combining the sampling control parameter set. The first fitting parameter set includes multiple sampling control parameters, and the sampling control parameters correspond one-to-one with the range of the control parameters.

[0053] Optionally, obtaining a reference decontamination assessment value using the target monitoring environment and water quality testing unit includes:

[0054] The target pollutant set is identified using the target monitoring environment. The target pollutant set includes multiple target pollutants. Multiple purification pollutant concentration groups are obtained based on the water quality detection unit, the target pollutant set, and the target monitoring environment. Each purification pollutant concentration group corresponds one-to-one with the target pollutants, and each purification pollutant concentration group includes multiple purification pollutant concentrations. The purification pollutant concentrations correspond one-to-one with the target fitting region corresponding to the target monitoring environment.

[0055] The target pollutants in the target detection pollutant set are scored to obtain a pollutant score value set, which includes multiple pollutant score values;

[0056] For each of the multiple purified pollutant concentration groups, perform the following operation:

[0057] The variance of the purified pollutant concentration is obtained based on the purified pollutant concentration group, wherein the variance of the purified pollutant concentration is the variance of the concentrations of multiple purified pollutants in the purified pollutant concentration group.

[0058] By comparing the variance of the purified pollutant concentration with a preset concentration variance threshold, and confirming that the variance of the purified pollutant concentration is less than or equal to the concentration variance threshold, a reference decontamination assessment value is calculated using a pollutant score set and multiple purified pollutant concentration groups.

[0059] Optionally, the calculation of the reference decontamination assessment value using a set of pollutant score values ​​and multiple groups of purified pollutant concentrations includes:

[0060] Multiple average concentrations of purified pollutants are obtained based on the multiple groups of purified pollutant concentrations, and multiple average initial pollutant concentrations are confirmed using the target monitoring environment, wherein the average initial pollutant concentration corresponds one-to-one with the average concentration of purified pollutants.

[0061] The reference decontamination assessment value is calculated using the average concentrations of multiple purified pollutants, the average concentrations of multiple initial pollutants, and a set of pollutant score values. The calculation formula is shown below:

[0062]

[0063] Where P represents the reference decontamination assessment value, b represents the number of b pollutant scores in the pollutant score set, and q a q w G represents the a-th and w-th pollutant score values ​​in the pollutant score value set, respectively. w f represents the average initial pollutant concentration among multiple average initial pollutant concentrations corresponding to the score value of the w-th pollutant. w This represents the average concentration of the purified pollutant that corresponds to the score value of the w-th pollutant among multiple average concentrations of purified pollutants.

[0064] Optionally, the step of identifying the target decontamination fitting parameter database based on reference decontamination assessment values ​​and target monitoring parameters includes:

[0065] Using pollutant names, a reference pollutant mean set is extracted from the updated monitoring cluster dataset. The reference pollutant mean set includes the mean values ​​of multiple target pollutants.

[0066] By associating the reference decontamination assessment value, the first set of fitting parameters, and the set of reference pollutant mean values, fitting data is obtained;

[0067] By summarizing the fitted data, a fitted dataset is obtained;

[0068] Using the reference decontamination assessment value as the dependent variable, a decontamination assessment surface is constructed using the fitted dataset. The decontamination assessment surface is then summarized to obtain the target decontamination fitting parameter database.

[0069] To address the above problems, the present invention also provides an electronic device, the electronic device comprising:

[0070] At least one processor; and,

[0071] A memory communicatively connected to the at least one processor; wherein,

[0072] The memory stores instructions that can be executed by the at least one processor, which are executed by the at least one processor to implement the above-described method for controlling initial rainwater pollution throughout the entire ecological process.

[0073] To address the aforementioned problems, the present invention also provides a computer-readable storage medium storing at least one instruction, which is executed by a processor in an electronic device to implement the above-described method for controlling initial rainwater pollution throughout the entire ecological process.

[0074] Compared to the problems described in the background art, the present invention identifies multiple experimental simulation area groups based on the area confirmation unit. It is evident that the embodiments of the present invention consider the characteristics of the experimental simulation area groups when confirming them, ensuring that the areas corresponding to the confirmed experimental simulation area groups meet the reliability requirements while eliminating accidental factors. Therefore, the target monitoring environment constructed using the experimental simulation area groups lays the foundation for the accuracy of the subsequently obtained reference decontamination assessment values. Furthermore, when confirming the experimental simulation area groups, the concentration of pollutants in different initial division areas is considered, and different relationships for calculating predicted pollutant concentrations are formulated based on the pollutant concentrations, making the calculated predicted pollutant concentrations more accurate. Moreover, the feasibility of the experimental simulation area groups is considered when confirming them. The feasibility refers to the fact that the area of ​​the target fitting area corresponding to the experimental simulation area group is the treatment area. This invention obtains target monitoring parameters based on the target monitoring environment, including reference rainfall time, reference rainfall pattern, and reference rainfall intensity. Reference decontamination assessment values ​​are obtained using the target monitoring environment and water quality testing units. Based on the reference decontamination assessment values ​​and target monitoring parameters, a target decontamination fitting parameter database is established. It is evident that this invention not only considers the pollution situation of the geological conditions corresponding to the simulated experimental area group but also the rainfall characteristics corresponding to the initial rainwater. Here, rainfall characteristics refer to the target monitoring parameters. Therefore, the target decontamination fitting parameter database, by comprehensively considering rainfall characteristics, pollution conditions, and the characteristics of different control schemes, can improve the intelligence and accuracy of initial rainwater pollution control in different areas. Therefore, the main purpose of the ecological whole-process initial rainwater pollution control method, device, electronic equipment, and computer-readable storage medium proposed in this invention is to improve the accuracy of initial rainwater pollution control. Attached Figure Description

[0075] Figure 1 A flowchart illustrating an ecological process for controlling initial rainwater pollution according to an embodiment of the present invention;

[0076] Figure 2 This is a schematic diagram of the structure of an electronic device for implementing the initial rainwater pollution control method throughout the entire ecological process, according to an embodiment of the present invention.

[0077] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0078] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0079] This application provides a method for controlling initial rainwater pollution throughout the entire ecological process. The implementing entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0080] Example 1:

[0081] Reference Figure 1 The diagram shown is a flowchart illustrating an ecological process-wide initial stormwater pollution control method according to an embodiment of the present invention. In this embodiment, the ecological process-wide initial stormwater pollution control method includes:

[0082] S1. Receive control instructions and confirm the pollution control environment based on the control instructions. The pollution control environment includes the target control area and the pollution control system. The pollution control system includes: area confirmation unit, parameter confirmation unit and water quality detection unit.

[0083] It should be explained that the control instructions refer to instructions used to control initial rainwater pollution in the target control area. Generally, control instructions are usually issued by personnel or departments that need to control initial rainwater pollution. The pollution control environment refers to the necessary environment for controlling initial rainwater pollution. The target control area refers to the area where initial rainwater pollution needs to be controlled. The pollution control system refers to an app or mini-program used to recommend or retrieve appropriate control methods or parameters required for control based on the characteristics of the target control area. The pollution control system includes an area confirmation unit, a parameter confirmation unit, and a water quality detection unit. Please refer to subsequent embodiments for specific applications of these units.

[0084] For example, Zhang, as the head of the environmental protection department, needs to control initial rainwater pollution in a designated area. Therefore, Zhang issues the control instruction and identifies the target control area and pollution control system. Through on-site investigation of the target control area, relevant characteristics are obtained, including the distribution of different pollutants. These characteristics are then input into the pollution control system, resulting in a sequence of ecological environment construction strategies recommended by the system based on these characteristics. This sequence includes multiple ecological environment construction strategies, including but not limited to: the type and scale of LID (Low Impact Development) facilities, wetlands... The invention considers factors such as plant species, density, and layout; the structure and materials of ecological revetments; the flow rate of initial rainwater discharge; and the retention time of initial rainwater at different locations. Combining this with the ecological environment construction strategy sequence and the actual environment of the target control area, Xiao Zhang selected a target environment construction strategy from the sequence and optimized the target control area accordingly. This optimized target control area refers to the area where appropriate facilities have been set up or appropriate wetland plants have been planted. Whenever rainfall occurs in the optimized target control area, rainfall characteristics are detected and predicted. The pollution control system can then recommend or execute appropriate control methods based on these characteristics. Therefore, this invention primarily aims to improve the accuracy of pollution control for initial rainwater by combining the relevant characteristics of the target control area with the rainfall characteristics of initial rainwater.

[0085] It should be explained that LID facilities refer to a series of stormwater management measures based on the low-impact development concept. LID facilities include, but are not limited to, green roofs, rain gardens, and sunken green spaces. Wetland plants refer to plants that grow in wetland environments. In this embodiment of the invention, wetland plants mainly serve to purify the water quality of initial rainwater. Ecological revetments refer to artificial waterfront revetments that restore the "permeability" of natural riverbanks. In this embodiment of the invention, ecological revetments mainly serve to purify the water quality of initial rainwater.

[0086] S2. Multiple experimental simulation region groups are identified based on the region confirmation unit, wherein the experimental simulation region group includes multiple experimental simulation regions.

[0087] It should be explained that the region confirmation unit identifies multiple experimental simulation region groups, including:

[0088] Upon receiving the region confirmation instruction from the region confirmation unit, the region confirmation instruction is parsed to obtain multiple initial proposed regions. For each of the multiple initial proposed regions, the following operations are performed:

[0089] The initially planned region is divided using a preset region division window to obtain multiple initial division regions. The following operations are performed on each of the multiple initial division regions:

[0090] The geometric center of the initial division region is identified, the reference coordinates of the geometric center are obtained, and the initial division region is marked using the reference coordinates to obtain marked division regions. The marked division regions are summarized to obtain multiple marked division regions, and each marked division region corresponds one-to-one with the initial division region.

[0091] The number of initial division regions in multiple initial division regions is counted to obtain the initial division number. The product of the preset extraction density ratio and the initial division number is calculated to obtain the region extraction number. Based on the region extraction number and the pre-constructed uniform sampling algorithm, multiple target detection regions are identified in multiple labeled division regions.

[0092] For each of the multiple target detection regions, perform the following operation:

[0093] The concentration groups of pollutants to be detected are obtained based on the target detection area. The concentration groups of pollutants to be detected include the concentrations of multiple pollutants with their names.

[0094] The detected pollutant concentration groups are summarized to obtain a set of detected pollutant concentration groups, and multiple experimental simulation region groups are obtained based on the set of detected pollutant concentration groups.

[0095] It should be understood that the initially designated area refers to the area used for experimentation; here, experimentation refers to an area where the ecological environment construction strategy can be implemented. For example, to test the actual effect of the ecological environment construction strategy, an area is planned where corresponding equipment can be installed or corresponding plants can be planted according to the ecological environment construction strategy, and water quality testing can be conducted. This area is the initially designated area. Generally, if an existing area with the same ecological environment construction strategy exists, the existing area can also be used as the target monitoring environment in subsequent embodiments.

[0096] Furthermore, a region partitioning window refers to an area with a specific shape and area. The region partitioning window is used to divide the initially planned region, thereby improving the accuracy of analysis for different initially partitioned regions. For example, if the initially planned region is a 2×2 rectangle and the region partitioning window is a 1×1 rectangle, then the initially planned region can be divided into four initial partitioned regions through the region partitioning window. Generally, the shape of the region partitioning window can be set in conjunction with the shape of the initially planned region. Once the shape and area of ​​the region partitioning window are confirmed, the geometric center of the initial partitioned region can be determined. For ease of understanding, a two-dimensional coordinate system is used as an example. For instance, if the initial partitioned region is a 1×1 rectangle, and the four vertices of this rectangle are (0, 0), (1, 1), (1, 0), and (0, 1), then the geometric center of this initial partitioned region is determined to be (0.5, 0.5). Optionally, image processing methods can be used to obtain the geometric center of the initial partitioned region; other techniques can achieve the same effect, which will not be elaborated upon here. Reference coordinates refer to the coordinates used to characterize the position of the geometric center. For example, with reference coordinates (1, 2, 3), the initial partitioned region can be identified using these coordinates as (1, 2, 3) - initial partitioned region, where (1, 2, 3) - initial partitioned region is the identified partitioned region. A uniform sampling algorithm is an algorithm that can uniformly extract multiple identified partitioned regions from multiple partitioned regions; the extracted identified partitioned regions are the target detection regions. Optionally, the uniform sampling algorithm is the Latin hypercube sampling method; other methods can achieve the same effect, and will not be elaborated further here. The purpose of using a uniform sampling algorithm is to uniformly select multiple target detection regions from multiple partitioned regions to improve the accuracy of subsequent pollutant prediction.

[0097] It is understood that the pollutant concentration refers to the concentration of substances capable of polluting water bodies. The pollutant name refers to the name used to characterize the pollutant; here, the pollutant name can be a specific name or a general term for a particular pollutant. For example, the pollutant name can be either a heavy metal or an organophosphate.

[0098] Furthermore, the acquisition of multiple experimental simulation region groups based on the detected pollutant concentration set includes:

[0099] The pollutant concentrations in each concentration set are summarized using the pollutant name, resulting in multiple analytical pollutant concentration sets. For each of these sets, the following operations are performed:

[0100] Multiple target prediction regions were identified across multiple labeled regions. The following operations were performed on each of these target prediction regions:

[0101] Based on the target prediction region, the pre-constructed pollution prediction formula and the analysis of pollutant concentration set, the predicted pollutant concentration is calculated, the predicted pollutant concentration is summarized to obtain the predicted pollutant concentration group, and the target prediction region is identified using the predicted pollutant concentration group to obtain the identified prediction region.

[0102] The target detection area is marked using the pollutant concentration group to obtain the marked detection area;

[0103] The target partitioning region set is obtained by summing the detected region and the predicted region. The target partitioning region set includes multiple target partitioning regions, and the target partitioning regions are the detected region or the predicted region.

[0104] A monitoring cluster dataset is extracted from the target segmented regions. This dataset contains multiple monitoring clusters, each corresponding one-to-one with a target segmented region. The monitoring cluster data is shown below:

[0105] C = (z, N1, N2, ..., N) H ,…,N M )

[0106] Where C represents the monitoring clustering data, z represents the reference coordinates corresponding to the target partitioned region, and N1, N2, N... H These represent the first, second, and Hth predicted pollutant concentrations in the predicted pollutant concentration group or the first, second, and Hth pollutant concentrations in the detected pollutant concentration group corresponding to the target area, respectively. M indicates that there are a total of M predicted pollutant concentrations or pollutant concentrations in the predicted pollutant concentration group or the detected pollutant concentration group.

[0107] Multiple experimental simulation region groups were obtained based on the monitoring clustering dataset and the target partitioning region set.

[0108] Understandably, the concentrations of pollutants with different names may be affected by the actual environment. Therefore, summarizing the concentrations of pollutants by name in separate detection pollutant concentration groups can improve the accuracy of predictions for specific pollutants in the target prediction area. A predicted pollutant concentration group refers to the set of pollutant concentrations obtained by predicting the concentrations of pollutants included in the target prediction area using an analyzed pollutant concentration set. The difference between a predicted pollutant concentration group and a detected pollutant concentration group is that the detected pollutant concentration group is obtained through on-site detection.

[0109] It should be understood that the pollution prediction formula is as follows:

[0110]

[0111] Among them, J i J represents the concentration of the i-th pollutant in the analysis of pollutant concentration concentrations. max d(Y0, Y0) represents the preset reference pollutant concentration, which is related to the name of the pollutant corresponding to the i-th pollutant concentration; t represents the preset proportion threshold; p0 represents the preset weight value; {} represents rounding up; Y0 represents the predicted pollutant concentration corresponding to the target prediction area; n represents the total number of pollutant concentrations in the analyzed pollutant concentration set; d(Y0, Y0) = 1. i ) represents the Euclidean distance between the reference coordinates corresponding to the target prediction area and the reference coordinates corresponding to the target detection area for the i-th pollutant concentration.

[0112] It should be explained that the reference pollutant concentration refers to the maximum value used to assess the pollution level caused by a pollutant concentration. The pollutant name corresponding to the reference concentration is the same as the pollutant name corresponding to the i-th pollutant concentration. Optionally, the reference pollutant concentration can be obtained through the national soil pollution risk management standard. Other techniques can achieve the same effect, and will not be elaborated further here. For example, if it is necessary to assess the concentration of heavy metals, i.e., the i-th pollutant concentration is the concentration of heavy metals, then when obtaining the reference pollutant concentration, the threshold for limiting the concentration of heavy metals can be obtained from the national soil pollution risk management standard, and this threshold can be used as the reference pollutant concentration.

[0113] Furthermore, when the ratio between the pollutant concentration and the reference pollutant concentration is large, meaning the ratio is greater than the aforementioned ratio threshold, it indicates that the pollutant concentration corresponding to the target detection area may have a significant impact on the surrounding target prediction area. Therefore, this embodiment of the invention improves the accuracy of pollutant concentration prediction for the target prediction area by dynamically adjusting the weight values.

[0114] Furthermore, the step of obtaining multiple experimental simulation region groups based on the monitoring clustering dataset and the target partitioning region set includes:

[0115] Using the pollutant names, multiple sets of analytical pollutant concentrations are extracted from the monitoring cluster dataset. Each set of analytical pollutant concentrations corresponds one-to-one with a pollutant name, and each set includes multiple analytical pollutant concentrations. The analytical pollutant concentrations are either predicted pollutant concentrations or pollutant concentrations, and each analytical pollutant concentration corresponds one-to-one with an initially defined region.

[0116] For each of the multiple analytical contaminant concentration sets, perform the following operation:

[0117] Based on the pollutant name, a pollution control threshold is obtained. Using the pollution control threshold, a pollution control concentration set is extracted from the analysis of the pollution concentration set. The pollution control concentration set includes multiple pollution control concentrations, and the pollution control concentration is greater than or equal to the pollution control threshold.

[0118] The number of pollution concentrations treated in a concentrated manner is statistically analyzed to obtain the number of treatment areas. The ratio of the number of treatment areas to the initial number of divisions is calculated to obtain the treatment area ratio.

[0119] If the proportion of the treated area is greater than or equal to the preset treatment proportion threshold, the monitoring cluster dataset is updated using the treated pollution concentration set to obtain the updated monitoring cluster dataset.

[0120] Otherwise, the analytical pollution concentrations corresponding to the analytical pollution concentration set are removed from the monitoring cluster dataset to obtain the updated monitoring cluster dataset;

[0121] Based on the updated monitoring clustering dataset and the target partitioning region set, multiple experimental simulation region groups were obtained.

[0122] It should be explained that the analyzed pollution concentration set refers to the set of concentrations of pollutants with the same pollutant name in the monitoring cluster dataset. The pollution control threshold is a threshold used to determine whether a pollutant needs to be controlled. The method for obtaining the pollution control threshold is the same as the method for obtaining the reference pollutant concentration, and will not be repeated here. Generally, when the proportion of the controlled area is less than the control proportion threshold, it indicates that the pollutant corresponding to that pollutant name in the initially proposed area that needs pollution control may be due to accidental factors. Updating the monitoring cluster dataset using the controlled pollution concentration set means replacing the concentration of the corresponding pollutant in the monitoring cluster dataset with the controlled pollution concentration set based on the pollutant name.

[0123] For example, the pollution concentration set includes three pollution concentrations, and the three pollution concentrations correspond to the first three monitoring clusters in the monitoring cluster dataset. After updating the monitoring cluster dataset using the pollution concentration set, only the first three monitoring clusters in the monitoring cluster dataset include the pollution concentrations, and the remaining monitoring clusters in the monitoring cluster dataset do not include the monitoring cluster data.

[0124] It should be explained that obtaining multiple experimental simulation region groups based on the updated monitoring clustering dataset and the target partitioning region set includes:

[0125] The update monitoring clustering dataset is clustered using a pre-built clustering algorithm to obtain multiple grouped datasets. The following operations are performed on each of the multiple grouped datasets:

[0126] Using the grouped dataset, the grouped partitioning region set is identified within the target partitioning region set;

[0127] Multiple target fitting regions are obtained based on the preset treatment area and the grouped region set, wherein the area corresponding to the target fitting region is the treatment area;

[0128] Based on the preset simulated classification values, multiple experimental simulation region groups are extracted from multiple target fitting regions. Each experimental simulation region group includes multiple experimental simulation regions, and the number of experimental simulation regions contained in each experimental simulation region group is the simulated classification value.

[0129] Furthermore, the clustering algorithm refers to an algorithm capable of clustering monitoring cluster data in the updated monitoring cluster dataset. Optionally, the k-means clustering algorithm is used as the clustering algorithm; other techniques can achieve the same effect, and will not be elaborated further here. The grouped dataset refers to the dataset obtained after clustering the updated monitoring cluster dataset using a clustering algorithm. For example, if the updated monitoring cluster dataset is clustered into 5 clusters using the k-means clustering algorithm, then the monitoring cluster data contained in each of the 5 clusters constitute the grouped dataset.

[0130] It should be explained that the grouped partition set is the set of regions identified in the target partition set from the grouped dataset. Generally, the grouped dataset includes multiple monitoring cluster data, and there is a one-to-one correspondence between the monitoring cluster data and the target partition regions in the target partition set. Therefore, the grouped partition set can be identified in the target partition set by the correspondence between the grouped data in the grouped dataset and the target partition regions in the target partition set.

[0131] It should be understood that the grouped regions identified using the grouped dataset may not be adjacent. When conducting pollution control assessments on non-adjacent regions, the results may be influenced by other regions, potentially leading to inaccurate assessments. Here, "region" refers to the target fitting region. Therefore, this embodiment of the invention requires the area corresponding to the target fitting region to be the treated area, thereby improving the practicality of the embodiment and the accuracy of subsequent pollution control assessments of the target fitting region. For ease of understanding, a two-dimensional coordinate system is used as an example. Each square region with a side length of 1 is the initial division region. The grouped region set includes four initial division regions, each consisting of three adjacent square regions and one independent square region. The preset treated area is 2. Using the treated area and the grouped region set, a target fitting region can be obtained. This target fitting region includes two square regions, which are the regions corresponding to two adjacent squares.

[0132] S3. Confirm receipt of parameter confirmation instruction from parameter confirmation unit, parse parameter confirmation instruction to obtain control parameter set, wherein control parameter set includes multiple control parameter ranges, obtain multiple first fitting parameter groups based on control parameter set, and obtain multiple matching nodes by combining multiple first fitting parameter groups and multiple experimental simulation region groups.

[0133] Furthermore, the range of controllable parameters refers to the range within which parameters in an ecological environment construction strategy can be adjusted, and this range is related to the facilities within the ecological environment construction strategy. For example, if a facility in an ecological environment construction strategy is a certain type of wetland plant, and the adjustable parameter is the density of the wetland plant, then the range of controllable parameters refers to the range of density of the wetland plant during planting. Generally, the facilities that can be arranged in an ecological environment construction strategy can be obtained through empirical methods. Once the ecological environment construction strategy is confirmed, the range of controllable parameters can be determined.

[0134] It should be explained that obtaining multiple first fitting parameter sets based on the control parameter set includes:

[0135] For each range of control parameters in the control parameter set, perform the following operation:

[0136] Using preset sampling values, uniform sampling is performed within the range of control parameters to obtain a sampling control parameter group, wherein the sampling control parameter group includes multiple sampling control parameters, and the number corresponding to the sampling control parameters is the sampling value;

[0137] The sampling control parameter sets are summarized to obtain a sampling control parameter set. Multiple first fitting parameter sets are obtained by combining the sampling control parameter set. The first fitting parameter set includes multiple sampling control parameters, and the sampling control parameters correspond one-to-one with the range of the control parameters.

[0138] For example, the sampling value is 5, and the control parameter range is 0 to 10. Uniform sampling can sample 1, 3, 5, 7 and 9 from the control parameter range. These 5 sampling control parameters constitute the sampling control parameter group.

[0139] S4. Construct a target monitoring environment based on the matching nodes.

[0140] It should be explained that constructing the target monitoring environment based on the matching nodes means: according to the sampling and control parameters corresponding to the first fitting parameter group in the matching nodes, constructing an ecological environment construction strategy corresponding to the first fitting parameter group in each experimental simulation area of ​​the experimental simulation area group. For example, the ecological environment construction strategy corresponding to the first fitting parameter group is: green roofs are used in all LID facilities, the type of wetland plant is cattail, and the density of wetland plants during planting is 55 plants / square meter. Then, using the ecological environment construction strategy, green roofs are laid in the experimental simulation area, and cattails are planted at a density of 55 plants / square meter in the wetland environment used for water purification.

[0141] S5. Obtain target monitoring parameters based on the target monitoring environment, wherein the target monitoring parameters include reference rainfall time, reference rainfall pattern and reference rainfall intensity, and obtain reference decontamination assessment values ​​using the target monitoring environment and water quality detection unit.

[0142] It should be explained that the reference rainfall time refers to the number of sunny days between the current rainfall and the previous rainfall, at the time the rainfall was detected. Generally, this embodiment of the invention obtains the data required for subsequent embodiments through experiments in a real environment, and this embodiment mainly aims to improve the accuracy of pollution control for initial rainwater. It is easy to understand that obtaining the reference decontamination assessment value presupposes rainfall in the target monitoring environment; here, the rainfall refers to the current rainfall. The reference rainfall pattern refers to the temporal distribution characteristics of the rainfall intensity during this rainfall. The reference rainfall intensity refers to the rainfall amount per unit time; in this embodiment of the invention, the target monitoring parameters all refer to the parameters corresponding to the initial rainwater. Optionally, the reference rainfall pattern is obtained through radar observation technology, and the technology for obtaining the reference rainfall pattern is existing technology and will not be elaborated here. The reference rainfall time can be obtained through statistical methods.

[0143] It is understood that obtaining reference decontamination assessment values ​​using the target monitoring environment and water quality testing unit includes:

[0144] The target pollutant set is identified using the target monitoring environment. The target pollutant set includes multiple target pollutants. Multiple purification pollutant concentration groups are obtained based on the water quality detection unit, the target pollutant set, and the target monitoring environment. Each purification pollutant concentration group corresponds one-to-one with the target pollutants, and each purification pollutant concentration group includes multiple purification pollutant concentrations. The purification pollutant concentrations correspond one-to-one with the target fitting region corresponding to the target monitoring environment.

[0145] The target pollutants in the target detection pollutant set are scored to obtain a pollutant score value set, which includes multiple pollutant score values;

[0146] For each of the multiple purified pollutant concentration groups, perform the following operation:

[0147] The variance of the purified pollutant concentration is obtained based on the purified pollutant concentration group, wherein the variance of the purified pollutant concentration is the variance of the concentrations of multiple purified pollutants in the purified pollutant concentration group.

[0148] By comparing the variance of the purified pollutant concentration with a preset concentration variance threshold, and confirming that the variance of the purified pollutant concentration is less than or equal to the concentration variance threshold, a reference decontamination assessment value is calculated using a pollutant score set and multiple purified pollutant concentration groups.

[0149] Furthermore, the target pollutant set refers to the set of pollutant names in the updated monitoring cluster dataset. The water quality detection unit refers to a unit or technology capable of detecting the pollutant content in initial rainwater. Optionally, near-infrared spectroscopy is used to detect the concentration of pollutants in initial rainwater; other technologies can achieve the same effect and will not be elaborated further here. The purpose of scoring the target pollutants is to distinguish the degree of environmental impact of different pollutants. Optionally, a 1-9 scale method is used to score the target pollutants. It should be noted that in this embodiment of the invention, a higher pollutant score indicates a higher degree of environmental impact. A concentration variance of purified pollutants less than or equal to the concentration variance threshold indicates the absence of randomness, thereby improving the accuracy of calculating the reference decontamination assessment value.

[0150] It should be understood that the calculation of the reference decontamination assessment value using the pollutant score set and multiple purification pollutant concentration groups includes:

[0151] Multiple average concentrations of purified pollutants are obtained based on the multiple groups of purified pollutant concentrations, and multiple average initial pollutant concentrations are confirmed using the target monitoring environment, wherein the average initial pollutant concentration corresponds one-to-one with the average concentration of purified pollutants.

[0152] The reference decontamination assessment value is calculated using the average concentrations of multiple purified pollutants, the average concentrations of multiple initial pollutants, and a set of pollutant score values. The calculation formula is shown below:

[0153]

[0154] Where P represents the reference decontamination assessment value, b represents the number of b pollutant scores in the pollutant score set, and q a q w G represents the a-th and w-th pollutant score values ​​in the pollutant score value set, respectively. w f represents the average initial pollutant concentration among multiple average initial pollutant concentrations corresponding to the score value of the w-th pollutant. w This represents the average concentration of the purified pollutant that corresponds to the score value of the w-th pollutant among multiple average concentrations of purified pollutants.

[0155] It should be explained that the initial average pollutant concentration refers to the average concentration of a certain pollutant corresponding to multiple target fitting areas in the target monitoring environment. Generally speaking, the smaller the average concentration of pollutants to be purified, the better the effect of pollution control in initial rainwater when adopting this ecological environment construction strategy. Therefore, in the embodiments of this invention, the larger the reference decontamination assessment value, the better the effect of pollution control in initial rainwater.

[0156] S6. Based on the reference decontamination assessment value and the target monitoring parameters, the target decontamination fitting parameter database is identified. The target decontamination fitting parameter database includes multiple target decontamination fitting parameter data, and the target decontamination fitting parameter data includes the reference area monitoring parameters, the target fitting parameter group, and the target monitoring parameters.

[0157] It should be explained that the database of target decontamination fitting parameters confirmed based on reference decontamination assessment values ​​and target monitoring parameters includes:

[0158] Using pollutant names, a reference pollutant mean set is extracted from the updated monitoring cluster dataset. The reference pollutant mean set includes the mean values ​​of multiple target pollutants.

[0159] By associating the reference decontamination assessment value, the first set of fitting parameters, and the set of reference pollutant mean values, fitting data is obtained;

[0160] By summarizing the fitted data, a fitted dataset is obtained;

[0161] Using the reference decontamination assessment value as the dependent variable, a decontamination assessment surface is constructed using the fitted dataset. The decontamination assessment surface is then summarized to obtain the target decontamination fitting parameter database.

[0162] Understandably, the target pollutant mean refers to the mean concentration of the pollutant corresponding to each pollutant name in the updated monitoring cluster dataset. Optionally, a decontamination assessment surface can be constructed using multinomial regression, with the reference decontamination assessment value in the fitted data as the dependent variable and the remaining parameters in the fitted data as independent variables.

[0163] Furthermore, the target decontamination fitting parameter data refers to the parameters corresponding to each decontamination assessment surface in the target decontamination fitting parameter database. Among them, the reference area monitoring parameters refer to the reference pollutant mean set, and the target fitting parameter group refers to the first fitting parameter group.

[0164] S7. Obtain the target area monitoring parameters and reference monitoring parameters of the target control area. Based on the target area monitoring parameters and reference monitoring parameters, retrieve the target control parameters from the target decontamination fitting parameter database to achieve initial rainwater pollution control in the target control area.

[0165] It should be explained that the definitions of the target area monitoring parameters and the reference area monitoring parameters are the same, and will not be repeated here. The definitions of the reference monitoring parameters and the target monitoring parameters are the same, and will not be repeated here. The difference between the reference monitoring parameters and the target monitoring parameters is that the reference monitoring parameters are parameters used to characterize rainfall patterns. These parameters are predicted values. Optionally, the parameters used to characterize rainfall patterns in the reference monitoring parameters can be obtained through a pre-trained neural network model. Other techniques can achieve the same effect, and will not be repeated here. Generally, when the target area monitoring parameters and reference monitoring parameters are not present in the target decontamination fitting parameter database, the decontamination assessment surfaces corresponding to parameters similar to the target area monitoring parameters and reference monitoring parameters can be identified in the target decontamination fitting parameter database, and the target control parameters can be identified on these decontamination assessment surfaces. The similar parameters can be obtained by calculating the Euclidean distance between the target area monitoring parameters and reference monitoring parameters and the parameters corresponding to each decontamination assessment surface, and taking the parameter corresponding to the smallest Euclidean distance as the similar parameter. Similarly, the number of decontamination assessment surfaces in the target decontamination fitting parameter database can be increased using existing technologies to enrich the target decontamination fitting parameter database. Optionally, after constructing the relationship between the dependent and independent variables through parametric modeling, different decontamination assessment surfaces can be obtained by changing the values ​​of the independent variables. Other techniques can achieve the same effect, which will not be elaborated here.

[0166] Furthermore, once the target area monitoring parameters and reference monitoring parameters are confirmed, the corresponding decontamination assessment surface can be retrieved from the target decontamination fitting parameter database using the target area monitoring parameters and reference monitoring parameters. The first fitting parameter group corresponding to the largest reference decontamination assessment value can be identified in the confirmed decontamination assessment surface, thus obtaining the target control parameters for pollution control of initial rainwater.

[0167] Compared to the problems described in the background art, the present invention identifies multiple experimental simulation area groups based on the area confirmation unit. It is evident that the embodiments of the present invention consider the characteristics of the experimental simulation area groups when confirming them, ensuring that the areas corresponding to the confirmed experimental simulation area groups meet the reliability requirements while eliminating accidental factors. Therefore, the target monitoring environment constructed using the experimental simulation area groups lays the foundation for the accuracy of the subsequently obtained reference decontamination assessment values. Furthermore, when confirming the experimental simulation area groups, the concentration of pollutants in different initial division areas is considered, and different relationships for calculating predicted pollutant concentrations are formulated based on the pollutant concentrations, making the calculated predicted pollutant concentrations more accurate. Moreover, the feasibility of the experimental simulation area groups is considered when confirming them. The feasibility refers to the fact that the area of ​​the target fitting area corresponding to the experimental simulation area group is the treatment area. This invention obtains target monitoring parameters based on the target monitoring environment, including reference rainfall time, reference rainfall pattern, and reference rainfall intensity. Reference decontamination assessment values ​​are obtained using the target monitoring environment and water quality testing units. Based on the reference decontamination assessment values ​​and target monitoring parameters, a target decontamination fitting parameter database is established. It is evident that this invention not only considers the pollution situation of the geological conditions corresponding to the simulated experimental area group but also the rainfall characteristics corresponding to the initial rainwater. Here, rainfall characteristics refer to the target monitoring parameters. Therefore, the target decontamination fitting parameter database, by comprehensively considering rainfall characteristics, pollution conditions, and the characteristics of different control schemes, can improve the intelligence and accuracy of initial rainwater pollution control in different areas. Therefore, the main purpose of the ecological whole-process initial rainwater pollution control method, device, electronic equipment, and computer-readable storage medium proposed in this invention is to improve the accuracy of initial rainwater pollution control.

[0168] Example 2:

[0169] like Figure 2 The diagram shown is a schematic representation of an electronic device for implementing an ecological full-process initial rainwater pollution control method according to an embodiment of the present invention.

[0170] The electronic device 1 may include a processor 10, a memory 11, a bus 12 and a communication interface 13, and may also include a computer program stored in the memory 11 and capable of running on the processor 10, such as an ecological process initial rainwater pollution control program.

[0171] The memory 11 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a portable hard drive. In other embodiments, the memory 11 can be an external storage device of the electronic device 1, such as a plug-in portable hard drive, SmartMediaCard (SMC), SecureDigital (SD) card, or FlashCard. Furthermore, the memory 11 can include both internal and external storage units of the electronic device 1. The memory 11 can be used not only to store application software and various types of data installed on the electronic device 1, such as the code for an ecological process-wide initial rainwater pollution control program, but also to temporarily store data that has been output or will be output.

[0172] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., a program for controlling initial rainwater pollution throughout the entire ecological process) and calls data stored in the memory 11 to perform various functions of the electronic device 1 and process data.

[0173] The bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable communication between the memory 11 and at least one processor 10, etc.

[0174] Figure 2 Only electronic devices with components are shown; it will be understood by those skilled in the art that... Figure 2The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0175] For example, although not shown, the electronic device 1 may also include a power supply (such as a battery) to power various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0176] Furthermore, the electronic 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 typically used to establish communication connections between the electronic device 1 and other electronic devices.

[0177] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired or 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) touchscreen. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device 1 and to display a visual user interface.

[0178] It should be understood that the embodiments described are for illustrative purposes only and are not limited to this structure in the scope of the patent application.

[0179] The initial rainwater pollution control program for the entire ecological process stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When run in the processor 10, it can achieve the following:

[0180] Receive control instructions and confirm the pollution control environment based on the control instructions. The pollution control environment includes the target control area and the pollution control system. The pollution control system includes: area confirmation unit, parameter confirmation unit and water quality detection unit.

[0181] Multiple experimental simulation region groups were identified based on the region identification unit, wherein each experimental simulation region group includes multiple experimental simulation regions;

[0182] The system confirms receipt of the parameter confirmation instruction from the parameter confirmation unit, parses the parameter confirmation instruction, and obtains a set of control parameters, wherein the set of control parameters includes multiple control parameter ranges. Based on the set of control parameters, multiple first fitting parameter groups are obtained. In a combined manner, multiple matching nodes are obtained using multiple first fitting parameter groups and multiple experimental simulation region groups. Each matching node includes one first fitting parameter group and one experimental simulation region group.

[0183] For each of the multiple matching nodes, perform the following operation:

[0184] A target monitoring environment is constructed based on the matching nodes;

[0185] Target monitoring parameters are obtained based on the target monitoring environment, including reference rainfall time, reference rainfall pattern and reference rainfall intensity. Reference decontamination assessment values ​​are obtained using the target monitoring environment and water quality detection unit.

[0186] Based on the reference decontamination assessment values ​​and target monitoring parameters, a target decontamination fitting parameter database was identified. The target decontamination fitting parameter database includes multiple target decontamination fitting parameter data, and the target decontamination fitting parameter data includes reference area monitoring parameters, target fitting parameter groups, and target monitoring parameters.

[0187] The target area monitoring parameters and reference monitoring parameters of the target control area are obtained. Based on the target area monitoring parameters and reference monitoring parameters, the target control parameters are retrieved from the target decontamination fitting parameter database to achieve the initial rainwater pollution control of the target control area.

[0188] Specifically, the processor 10's implementation method for the above instructions can be found in [reference needed]. Figures 1 to 2 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0189] Furthermore, if the modules / units integrated in the electronic device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0190] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor of an electronic device, can perform the following:

[0191] Receive control instructions and confirm the pollution control environment based on the control instructions. The pollution control environment includes the target control area and the pollution control system. The pollution control system includes: area confirmation unit, parameter confirmation unit and water quality detection unit.

[0192] Multiple experimental simulation region groups were identified based on the region identification unit, wherein each experimental simulation region group includes multiple experimental simulation regions;

[0193] The system confirms receipt of the parameter confirmation instruction from the parameter confirmation unit, parses the parameter confirmation instruction, and obtains a set of control parameters, wherein the set of control parameters includes multiple control parameter ranges. Based on the set of control parameters, multiple first fitting parameter groups are obtained. In a combined manner, multiple matching nodes are obtained using multiple first fitting parameter groups and multiple experimental simulation region groups. Each matching node includes one first fitting parameter group and one experimental simulation region group.

[0194] For each of the multiple matching nodes, perform the following operation:

[0195] A target monitoring environment is constructed based on the matching nodes;

[0196] Target monitoring parameters are obtained based on the target monitoring environment, including reference rainfall time, reference rainfall pattern and reference rainfall intensity. Reference decontamination assessment values ​​are obtained using the target monitoring environment and water quality detection unit.

[0197] Based on the reference decontamination assessment values ​​and target monitoring parameters, a target decontamination fitting parameter database was identified. The target decontamination fitting parameter database includes multiple target decontamination fitting parameter data, and the target decontamination fitting parameter data includes reference area monitoring parameters, target fitting parameter groups, and target monitoring parameters.

[0198] The target area monitoring parameters and reference monitoring parameters of the target control area are obtained. Based on the target area monitoring parameters and reference monitoring parameters, the target control parameters are retrieved from the target decontamination fitting parameter database to achieve the initial rainwater pollution control of the target control area.

[0199] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0200] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0201] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0202] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for controlling initial rainwater pollution throughout the entire ecological process, characterized in that, The method includes: Receive control instructions and confirm the pollution control environment based on the control instructions. The pollution control environment includes the target control area and the pollution control system. The pollution control system includes: area confirmation unit, parameter confirmation unit and water quality detection unit. Multiple experimental simulation region groups were identified based on the region identification unit, wherein each experimental simulation region group includes multiple experimental simulation regions; The system confirms receipt of the parameter confirmation instruction from the parameter confirmation unit, parses the parameter confirmation instruction, and obtains a set of control parameters, wherein the set of control parameters includes multiple control parameter ranges. Based on the set of control parameters, multiple first fitting parameter groups are obtained. In a combined manner, multiple matching nodes are obtained using multiple first fitting parameter groups and multiple experimental simulation region groups. Each matching node includes one first fitting parameter group and one experimental simulation region group. For each of the multiple matching nodes, perform the following operation: A target monitoring environment is constructed based on the matching nodes; Target monitoring parameters are obtained based on the target monitoring environment, including reference rainfall time, reference rainfall pattern, and reference rainfall intensity. Reference decontamination assessment values ​​are then obtained using the target monitoring environment and water quality testing unit. The method for obtaining the reference decontamination assessment values ​​is as follows: The reference decontamination assessment value is calculated using the average concentrations of multiple purified pollutants, the average concentrations of multiple initial pollutants, and a set of pollutant score values. The calculation formula is shown below: ， in, This indicates the reference decontamination assessment value. This indicates that the pollutant score set contains a total of Each pollutant score value, , These represent the first pollutant score in the set. The, the Each pollutant score value, This indicates that among multiple initial pollutant concentration averages, the one that is most similar to the first... The average initial pollutant concentration corresponding to each pollutant score value. This indicates that among the average concentrations of multiple purified pollutants, the one with the highest concentration is... The average concentration of pollutants to be purified corresponding to each pollutant score value; Based on the reference decontamination assessment values ​​and target monitoring parameters, a target decontamination fitting parameter database was identified. The target decontamination fitting parameter database includes multiple target decontamination fitting parameter data, and the target decontamination fitting parameter data includes reference area monitoring parameters, target fitting parameter groups, and target monitoring parameters. The target area monitoring parameters and reference monitoring parameters of the target control area are obtained. Based on the target area monitoring parameters and reference monitoring parameters, the target control parameters are retrieved from the target decontamination fitting parameter database to achieve the initial rainwater pollution control of the target control area.

2. The method for controlling initial rainwater pollution throughout the entire ecological process as described in claim 1, characterized in that, The region confirmation unit identifies multiple experimental simulation region groups, including: Upon receiving the region confirmation instruction from the region confirmation unit, the region confirmation instruction is parsed to obtain multiple initial proposed regions. For each of the multiple initial proposed regions, the following operations are performed: The initially planned region is divided using a preset region division window to obtain multiple initial division regions. The following operations are performed on each of the multiple initial division regions: The geometric center of the initial division region is identified, the reference coordinates of the geometric center are obtained, and the initial division region is marked using the reference coordinates to obtain marked division regions. The marked division regions are summarized to obtain multiple marked division regions, and each marked division region corresponds one-to-one with the initial division region. The number of initial division regions in multiple initial division regions is counted to obtain the initial division number. The product of the preset extraction density ratio and the initial division number is calculated to obtain the region extraction number. Based on the region extraction number and the pre-constructed uniform sampling algorithm, multiple target detection regions are identified in multiple labeled division regions. For each of the multiple target detection regions, perform the following operation: The concentration groups of pollutants to be detected are obtained based on the target detection area. The concentration groups of pollutants to be detected include the concentrations of multiple pollutants with their names. The detected pollutant concentration groups are summarized to obtain a set of detected pollutant concentration groups, and multiple experimental simulation region groups are obtained based on the set of detected pollutant concentration groups.

3. The method for controlling initial rainwater pollution throughout the entire ecological process as described in claim 2, characterized in that, The process of obtaining multiple experimental simulation region groups based on the detected pollutant concentration set includes: The pollutant concentrations in each concentration set are summarized using the pollutant name, resulting in multiple analytical pollutant concentration sets. For each of these sets, the following operations are performed: Multiple target prediction regions were identified across multiple labeled regions. The following operations were performed on each of these target prediction regions: Based on the target prediction region, the pre-constructed pollution prediction formula and the analysis of pollutant concentration set, the predicted pollutant concentration is calculated, the predicted pollutant concentration is summarized to obtain the predicted pollutant concentration group, and the target prediction region is identified using the predicted pollutant concentration group to obtain the identified prediction region. The target detection area is marked using the pollutant concentration group to obtain the marked detection area; The target partitioning region set is obtained by summing the detected region and the predicted region. The target partitioning region set includes multiple target partitioning regions, and the target partitioning regions are the detected region or the predicted region. A monitoring cluster dataset is extracted from the target segmented regions. This dataset contains multiple monitoring clusters, each corresponding one-to-one with a target segmented region. The monitoring cluster data is shown below: ， in, This indicates monitoring clustering data. This represents the reference coordinates corresponding to the target region. , , These respectively represent the first, second, and third predicted pollutant concentration groups corresponding to the target area. The first, second, and third groups of predicted or detected pollutant concentrations Concentration of each pollutant, This indicates that there are a total of [number] pollutant concentration groups or pollutant concentration detection groups. A predicted pollutant concentration or pollutant concentration; Multiple experimental simulation region groups were obtained based on the monitoring clustering dataset and the target partitioning region set.

4. The method for controlling initial rainwater pollution throughout the entire ecological process as described in claim 3, characterized in that, The pollution prediction relationship is shown below: ， in, This indicates the concentration of pollutants analyzed. Concentration of each pollutant, This indicates a preset reference pollutant concentration, and the reference pollutant concentration is related to the first... The concentration of each pollutant is related to the name of the pollutant. This indicates a preset proportional threshold. This indicates the preset weight value. Indicates rounding up. This indicates the predicted pollutant concentration corresponding to the target prediction area. This indicates that the concentration of pollutants analyzed is concentrated in a total of Concentration of each pollutant, Indicates the reference coordinates corresponding to the target prediction area and the first The Euclidean distance of the reference coordinates of the target detection area corresponding to each pollutant concentration.

5. The method for controlling initial rainwater pollution throughout the entire ecological process as described in claim 4, characterized in that, The process of obtaining multiple experimental simulation region groups based on the monitoring clustering dataset and the target region segmentation set includes: Using the pollutant names, multiple sets of analytical pollutant concentrations are extracted from the monitoring cluster dataset. Each set of analytical pollutant concentrations corresponds one-to-one with a pollutant name, and each set includes multiple analytical pollutant concentrations. The analytical pollutant concentrations are either predicted pollutant concentrations or pollutant concentrations, and each analytical pollutant concentration corresponds one-to-one with an initially defined region. For each of the multiple analytical contaminant concentration sets, perform the following operation: Based on the pollutant name, a pollution control threshold is obtained. Using the pollution control threshold, a pollution control concentration set is extracted from the analysis of the pollution concentration set. The pollution control concentration set includes multiple pollution control concentrations, and the pollution control concentration is greater than or equal to the pollution control threshold. The number of pollution concentrations treated in a concentrated manner is statistically analyzed to obtain the number of treatment areas. The ratio of the number of treatment areas to the initial number of divisions is calculated to obtain the treatment area ratio. If the proportion of the treated area is greater than or equal to the preset treatment proportion threshold, the monitoring cluster dataset is updated using the treated pollution concentration set to obtain the updated monitoring cluster dataset. Otherwise, the analytical pollution concentrations corresponding to the analytical pollution concentration set are removed from the monitoring cluster dataset to obtain the updated monitoring cluster dataset; Based on the updated monitoring clustering dataset and the target partitioning region set, multiple experimental simulation region groups were obtained.

6. The method for controlling initial rainwater pollution throughout the entire ecological process as described in claim 5, characterized in that, The process of obtaining multiple experimental simulation region groups based on the updated monitoring clustering dataset and the target partitioned region set includes: The update monitoring clustering dataset is clustered using a pre-built clustering algorithm to obtain multiple grouped datasets. The following operations are performed on each of the multiple grouped datasets: Using the grouped dataset, the grouped partitioning region set is identified within the target partitioning region set; Multiple target fitting regions are obtained based on the preset treatment area and the grouped region set, wherein the area corresponding to the target fitting region is the treatment area; Based on the preset simulated classification values, multiple experimental simulation region groups are extracted from multiple target fitting regions. Each experimental simulation region group includes multiple experimental simulation regions, and the number of experimental simulation regions contained in each experimental simulation region group is the simulated classification value.

7. The method for controlling initial rainwater pollution throughout the entire ecological process as described in claim 6, characterized in that, The process of obtaining multiple first fitting parameter sets based on the control parameter set includes: For each range of control parameters in the control parameter set, perform the following operation: Using preset sampling values, uniform sampling is performed within the range of control parameters to obtain a sampling control parameter group, wherein the sampling control parameter group includes multiple sampling control parameters, and the number corresponding to the sampling control parameters is the sampling value; The sampling control parameter sets are summarized to obtain a sampling control parameter set. Multiple first fitting parameter sets are obtained by combining the sampling control parameter set. The first fitting parameter set includes multiple sampling control parameters, and the sampling control parameters correspond one-to-one with the range of the control parameters.

8. The method for controlling initial rainwater pollution throughout the entire ecological process as described in claim 7, characterized in that, Before obtaining the reference decontamination assessment value using the target monitoring environment and water quality testing unit, the method further includes: The target pollutant set is identified using the target monitoring environment. The target pollutant set includes multiple target pollutants. Multiple purification pollutant concentration groups are obtained based on the water quality detection unit, the target pollutant set, and the target monitoring environment. Each purification pollutant concentration group corresponds one-to-one with the target pollutants, and each purification pollutant concentration group includes multiple purification pollutant concentrations. The purification pollutant concentrations correspond one-to-one with the target fitting region corresponding to the target monitoring environment. The target pollutants in the target detection pollutant set are scored to obtain a pollutant score value set, which includes multiple pollutant score values; For each of the multiple purified pollutant concentration groups, perform the following operation: The variance of the purified pollutant concentration is obtained based on the purified pollutant concentration group, wherein the variance of the purified pollutant concentration is the variance of the concentrations of multiple purified pollutants in the purified pollutant concentration group. By comparing the variance of the purified pollutant concentration with a preset concentration variance threshold, and confirming that the variance of the purified pollutant concentration is less than or equal to the concentration variance threshold, a reference decontamination assessment value is calculated using a pollutant score set and multiple purified pollutant concentration groups.

9. The method for controlling initial rainwater pollution throughout the entire ecological process as described in claim 8, characterized in that, Before calculating the reference decontamination assessment value using the pollutant score set and multiple purification pollutant concentration groups, the following steps are also included: Multiple average concentrations of purified pollutants are obtained based on the multiple groups of purified pollutant concentrations, and multiple average initial pollutant concentrations are confirmed using the target monitoring environment, wherein the average initial pollutant concentration corresponds one-to-one with the average concentration of purified pollutants.

10. The method for controlling initial rainwater pollution throughout the entire ecological process as described in claim 9, characterized in that, The target decontamination fitting parameter database, determined based on reference decontamination assessment values ​​and target monitoring parameters, includes: Using pollutant names, a reference pollutant mean set is extracted from the updated monitoring cluster dataset. The reference pollutant mean set includes the mean values ​​of multiple target pollutants. By associating the reference decontamination assessment value, the first set of fitting parameters, and the set of reference pollutant mean values, fitting data is obtained; By summarizing the fitted data, a fitted dataset is obtained; Using the reference decontamination assessment value as the dependent variable, a decontamination assessment surface is constructed using the fitted dataset. The decontamination assessment surface is then summarized to obtain the target decontamination fitting parameter database.

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