Ecological whole-process initial rainwater pollution management and control method

Abstract

The invention relates to the technical field of pollution control, and discloses an ecological whole-process initial rainwater pollution control method, which comprises the following steps: determining a target control area and a pollution control system, determining a plurality of experimental simulation area groups, obtaining a plurality of matching nodes based on a control parameter set, constructing a target monitoring environment based on the matching nodes, and monitoring the target monitoring environment according to the target monitoring environment. Acquiring target monitoring parameters based on a target monitoring environment, acquiring a reference decontamination evaluation value by using the target monitoring environment and a water quality detection unit, determining a target decontamination fitting parameter database based on the reference decontamination evaluation value and the target monitoring parameters, and acquiring target area monitoring parameters and reference monitoring parameters of a target management and control area, and based on the target area monitoring parameters and the reference monitoring parameters, target management and control parameters are retrieved from the target decontamination fitting parameter database, and initial rainwater pollution management and control of the target management and control area are realized. The main purpose of the invention is to improve the accuracy of pollution management and control of initial rainwater.

Description

Technical Field

[0001] The present invention relates to an ecological whole-process initial rainwater pollution control method, belonging to the technical field of pollution treatment. Background Art

[0002] With the acceleration of the urbanization process, the problem of urban rainwater pollution has become increasingly serious. A large amount of pollutants are often carried in the initial rainwater. Therefore, the initial rainwater may cause problems such as water eutrophication. Correspondingly, how to improve the accuracy of pollution control for the initial rainwater has become an urgent problem to be solved.

[0003] At present, for rainwater pollution control, the laying of initial rainwater pollution control equipment is mostly based on experience, and the pollution control of the initial rainwater is realized in combination with experience.

[0004] Although the above method can realize the pollution control of the initial rainwater, when carrying out the pollution control of the initial rainwater, the characteristics of pollutants in the control area to be controlled and the characteristics of pollutants that different facilities can handle are not considered. Therefore, using the empirical method to lay the initial rainwater pollution control equipment and treat the initial rainwater for pollution may lead to inaccurate pollution control of the initial rainwater. Summary of the Invention

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

[0006] To achieve the above object, an ecological whole-process initial rainwater pollution control method provided by the present invention includes:

[0007] Receiving a control instruction, and confirming a pollution control environment based on the control instruction, wherein the pollution control environment includes a target control area and a pollution control system, and the pollution control system includes: an area confirmation unit, a parameter confirmation unit and a water quality detection unit;

[0008] Confirming a plurality of experimental simulation area groups based on the area confirmation unit, wherein each experimental simulation area group includes a plurality of experimental simulation areas;

[0009] Confirming to receive a parameter confirmation instruction from the parameter confirmation unit, parsing the parameter confirmation instruction to obtain a set of regulation parameters, wherein the set of regulation parameters includes a plurality of regulation parameter ranges, obtaining a plurality of first fitting parameter groups based on the set of regulation parameters, and in a combined manner, using the plurality of first fitting parameter groups and the plurality of experimental simulation area groups to obtain a plurality of matching nodes, wherein each matching node includes a first fitting parameter group and an experimental simulation area group;

[0010] Perform the following operations for each of the multiple matching nodes:

[0011] Construct a target monitoring environment based on the matching node;

[0012] Obtain target monitoring parameters based on the target monitoring environment, where the target monitoring parameters include reference rainfall time, reference rainfall pattern, and reference rainfall intensity, and obtain a reference decontamination evaluation value by using the target monitoring environment and a water quality detection unit;

[0013] Confirm a target decontamination fitting parameter database based on the reference decontamination evaluation value and the target monitoring parameters, where 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] Obtain target area monitoring parameters and reference monitoring parameters of a target control area, and retrieve target control parameters in the target decontamination fitting parameter database based on the target area monitoring parameters and the reference monitoring parameters to realize the control of the initial rainwater pollution in the target control area.

[0015] Optionally, the confirmation of multiple experimental simulation area groups by the area confirmation unit includes:

[0016] Confirm and receive an area confirmation instruction from the area confirmation unit, parse the area confirmation instruction to obtain multiple initial proposed areas, and perform the following operations for each of the multiple initial proposed areas:

[0017] Divide the initial proposed area by using a preset area division window to obtain multiple initial divided areas, and perform the following operations for each of the multiple initial divided areas:

[0018] Confirm the geometric center of the initial divided area, obtain the reference coordinates of the geometric center, use the reference coordinates to identify the initial divided area to obtain an identified divided area, summarize the identified divided areas to obtain multiple identified divided areas, and the identified divided areas correspond to the initial divided areas one by one;

[0019] Count the number of initial divided areas in the multiple initial divided areas to obtain an initial division number, calculate the product of a preset extraction density ratio and the initial division number to obtain an area extraction number, and confirm multiple target detection areas in the multiple identified divided areas based on the area extraction number and a pre-constructed uniform sampling algorithm;

[0020] Perform the following operations for each of the multiple target detection areas:

[0021] Obtain a set of detected pollutant concentrations based on the target detection area, where the set of detected pollutant concentrations includes multiple pollutant concentrations labeled with pollutant names;

[0022] Summarize the set of detected pollutant concentrations to obtain a set of detected pollutant concentration sets, and obtain multiple experimental simulation area sets based on the set of detected pollutant concentration sets.

[0023] Optionally, the obtaining of multiple experimental simulation area sets based on the set of detected pollutant concentration sets includes:

[0024] Summarize the pollutant concentrations in the set of detected pollutant concentration sets using the pollutant names respectively to obtain multiple sets of analyzed pollutant concentrations, and perform the following operations on each set of analyzed pollutant concentrations in the multiple sets of analyzed pollutant concentrations:

[0025] Identify multiple target prediction areas in the multiple labeled division areas, and perform the following operations on each target prediction area in the multiple target prediction areas:

[0026] Calculate the predicted pollutant concentration based on the target prediction area, the pre-constructed pollution prediction relationship formula, and the set of analyzed pollutant concentrations, summarize the predicted pollutant concentrations to obtain a set of predicted pollutant concentrations, and use the set of predicted pollutant concentrations to label the target prediction area to obtain a labeled prediction area;

[0027] Use the set of detected pollutant concentrations to label the target detection area to obtain a labeled detection area;

[0028] Summarize the labeled detection area and the labeled prediction area to obtain a set of target division areas, where the set of target division areas includes multiple target division areas, and the target division area is the labeled detection area or the labeled prediction area;

[0029] Extract a monitoring clustering data set from the set of target division areas, where the monitoring clustering data set includes multiple monitoring clustering data, and the monitoring clustering data corresponds one-to-one with the target division area, and the monitoring clustering data is as follows:

[0030] C=(z,N1,N2,…,N[[ID=:28]] H ,…,N M )

[0031] Where C represents the monitoring clustering data, z represents the reference coordinate corresponding to the target division area, and N1, N2, N H respectively represent the first, second, and Hth predicted pollutant concentrations in the set of predicted pollutant concentrations corresponding to the target division area or the first, second, and Hth pollutant concentrations in the set of detected pollutant concentrations, and M represents that there are M predicted pollutant concentrations or pollutant concentrations in the set of predicted pollutant concentrations or the set of detected pollutant concentrations;

[0032] Obtain a plurality of experimental simulation region groups based on the monitoring clustering data set and the target division region set.

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

[0034]

[0035] Where J i represents the i-th pollutant concentration in the analysis of pollutant concentration concentration, J max represents the preset reference pollutant concentration, and the reference pollutant concentration is related to the pollutant name corresponding to the i-th pollutant concentration, t represents the preset ratio threshold, p0 represents the preset weight value, {} represents rounding up, Y0 represents the predicted pollutant concentration corresponding to the target prediction region, n represents that there are n pollutant concentrations in the analysis of pollutant concentration concentration, and d(Y0, Y i ) represents the Euclidean distance between the reference coordinates corresponding to the target prediction region and the reference coordinates of the target detection region corresponding to the i-th pollutant concentration.

[0036] Optionally, the obtaining of a plurality of experimental simulation region groups based on the monitoring clustering data set and the target division region set includes:

[0037] Extract a plurality of analysis pollution concentration sets from the monitoring clustering data set by using the pollutant name, wherein the analysis pollution concentration sets correspond one-to-one with the pollutant name, and the analysis pollution concentration set includes a plurality of analysis pollutant concentrations, the analysis pollutant concentration is the predicted pollutant concentration or the pollutant concentration, and the analysis pollutant concentration corresponds one-to-one with the initial division region;

[0038] Perform the following operations on each analysis pollution concentration set in the plurality of analysis pollution concentration sets:

[0039] Obtain a pollution control threshold based on the pollutant name, and use the pollution control threshold to extract a control pollution concentration set from the analysis pollution concentration set, wherein the control pollution concentration set includes a plurality of control pollution concentrations, and the control pollution concentration is greater than or equal to the pollution control threshold;

[0040] Count the number of control pollution concentrations in the control pollution concentration set to obtain the number of control regions, and calculate the ratio of the number of control regions to the initial division number to obtain the control region ratio;

[0041] If the control region ratio is greater than or equal to the preset control ratio threshold, then update the monitoring clustering data set with the control pollution concentration set to obtain an updated monitoring clustering data set;

[0042] Otherwise, remove the analysis pollution concentrations corresponding to the analysis pollution concentration set from the monitoring clustering dataset to obtain an updated monitoring clustering dataset;

[0043] Obtain multiple experimental simulation area groups based on the updated monitoring clustering dataset and the target division area set.

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

[0045] Use a pre-constructed clustering algorithm to cluster the updated monitoring clustering dataset to obtain multiple grouped datasets, and perform the following operations on each grouped dataset in the multiple grouped datasets:

[0046] Use the grouped dataset to identify a grouped division area set in the target division area set;

[0047] Obtain multiple target fitting areas based on a preset treatment area and the grouped division area set, where the areas corresponding to the target fitting areas are all the treatment area;

[0048] Extract multiple experimental simulation area groups from the multiple target fitting areas based on a preset simulation classification value, where each experimental simulation area group includes multiple experimental simulation areas, and the number of experimental simulation areas included in the experimental simulation area group is the simulation classification value.

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

[0050] Perform the following operations on each regulation parameter range in the regulation parameter set:

[0051] Use a preset sampling value to perform uniform sampling in the regulation parameter range to obtain a sampled regulation parameter group, where the sampled regulation parameter group includes multiple sampled regulation parameters, and the number of sampled regulation parameters corresponds to the sampling value;

[0052] Summarize the sampled regulation parameter groups to obtain a set of sampled regulation parameter groups, and in a combined manner, use the set of sampled regulation parameter groups to obtain multiple first fitting parameter groups, where each first fitting parameter group includes multiple sampled regulation parameters, and the sampled regulation parameters correspond one-to-one with the regulation parameter ranges.

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

[0054] Identify a set of target detection pollutants using the target monitoring environment. The set of target detection pollutants includes multiple target detection pollutants. Obtain multiple sets of purified pollutant concentrations based on the water quality detection unit, the set of target detection pollutants, and the target monitoring environment. The sets of purified pollutant concentrations correspond one-to-one with the target detection pollutants, and each set of purified pollutant concentrations includes multiple purified pollutant concentrations. The purified pollutant concentrations correspond one-to-one with the target fitting regions corresponding to the target monitoring environment.

[0055] Score the target detection pollutants in the set of target detection pollutants to obtain a set of pollutant score values, where the set of pollutant score values includes multiple pollutant score values.

[0056] Perform the following operations on each set of purified pollutant concentrations in the multiple sets of purified pollutant concentrations:

[0057] Obtain the variance of the purified pollutant concentrations based on the set of purified pollutant concentrations, where the variance of the purified pollutant concentrations is the variance of the multiple purified pollutant concentrations in the set of purified pollutant concentrations.

[0058] Compare the variance of the purified pollutant concentrations with a preset concentration variance threshold. After confirming that the variance of the purified pollutant concentrations is less than or equal to the concentration variance threshold, calculate a reference decontamination evaluation value using the set of pollutant score values and the multiple sets of purified pollutant concentrations.

[0059] Optionally, calculating the reference decontamination evaluation value using the set of pollutant score values and the multiple sets of purified pollutant concentrations includes:

[0060] Obtain multiple average values of purified pollutant concentrations based on the multiple sets of purified pollutant concentrations, and identify multiple initial average pollutant concentrations using the target monitoring environment. The initial average pollutant concentrations correspond one-to-one with the average values of the purified pollutant concentrations.

[0061] Calculate the reference decontamination evaluation value using the multiple average values of purified pollutant concentrations, the multiple initial average pollutant concentrations, and the set of pollutant score values. The calculation formula is as follows:

[0062]

[0063] Where P represents the reference decontamination evaluation value, b represents that there are b pollutant score values in the set of pollutant score values, q a 、q w represent the a-th and w-th pollutant score values in the set of pollutant score values respectively, g w represents the initial average pollutant concentration corresponding to the w-th pollutant score value among the multiple initial average pollutant concentrations, and f w represents the average value of the purified pollutant concentration corresponding to the w-th pollutant score value among the multiple average values of the purified pollutant concentrations.

[0064] Optionally, the target decontamination fitting parameter database confirmed based on the reference decontamination evaluation value and the target monitoring parameter includes:

[0065] Using the pollutant names, extract the reference pollutant mean set from the updated monitoring clustering dataset, where the reference pollutant mean set includes multiple target pollutant means;

[0066] Associate the reference decontamination evaluation value, the first fitting parameter group, and the reference pollutant mean set to obtain fitting data;

[0067] Summarize the fitting data to obtain a fitting dataset;

[0068] Taking the reference decontamination evaluation value as the dependent variable, construct a decontamination evaluation surface using the fitting dataset, and summarize the decontamination evaluation surface to obtain the target decontamination fitting parameter database.

[0069] To solve the above problems, the present invention also provides an electronic device, which includes:

[0070] At least one processor; and,

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

[0072] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to implement the above-mentioned ecological whole-process initial rainwater pollution control method.

[0073] To solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one instruction is stored, and the at least one instruction is executed by a processor in an electronic device to implement the above-mentioned ecological whole-process initial rainwater pollution control method.

[0074] Compared with the problems described in the background art, the present invention confirms multiple experimental simulation area groups based on the area confirmation unit. It can be seen that the embodiments of the present invention consider the characteristics of the experimental simulation area groups when confirming the experimental simulation area groups, so that the areas corresponding to the confirmed experimental simulation area groups meet the credibility while excluding accidental factors. Therefore, the target monitoring environment constructed by using the experimental simulation area groups lays a foundation for the accuracy of the reference decontamination evaluation value obtained subsequently. When confirming the experimental simulation area groups, the concentration of pollutants in different initially divided areas is considered, and different relational expressions for calculating the predicted pollutant concentration are formulated in combination with the concentration of pollutants, so that the calculated predicted pollutant concentration is more accurate. When confirming the experimental simulation area groups, the feasibility of the experimental simulation area groups is also considered. Here, the feasibility means that the areas of the target fitting areas corresponding to the experimental simulation area groups are all the treatment areas. The present invention obtains target monitoring parameters based on the target monitoring environment, where the target monitoring parameters include the reference rainfall time, reference rainfall pattern, and reference rainfall intensity. The reference decontamination evaluation value is obtained by using the target monitoring environment and the water quality detection unit. The target decontamination fitting parameter database is confirmed based on the reference decontamination evaluation value and the target monitoring parameters. It can be seen that the present invention not only considers the pollution situation of the geology corresponding to the simulation experimental area groups, but also considers the rainfall characteristics corresponding to the initial rainwater. Here, the rainfall characteristics refer to the target monitoring parameters. Furthermore, the target decontamination fitting parameter database can improve the intelligence and accuracy of the initial rainwater pollution control for different regions by comprehensively considering the rainfall characteristics, pollution situation, and characteristics of different control schemes. Therefore, the ecological whole-process initial rainwater pollution control method, device, electronic device, and computer-readable storage medium proposed by the present invention mainly aim to improve the accuracy of the pollution control of the initial rainwater. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 It is a flowchart of the ecological whole-process initial rainwater pollution control method provided by an embodiment of the present invention;

[0076] Figure 2 It is a structural diagram of an electronic device for implementing the ecological whole-process initial rainwater pollution control method provided by an embodiment of the present invention.

[0077] The implementation, functional features, and advantages of the present invention will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0078] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0079] The embodiments of the present application provide an ecological method for controlling the pollution of early rainwater throughout the whole process. The execution subject of the ecological method for controlling the pollution of early rainwater throughout the whole process includes, but is not limited to, at least one of electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided by the embodiments of the present application. In other words, the ecological method for controlling the pollution of early rainwater throughout the whole process 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, etc.

[0080] Embodiment 1:

[0081] Refer to Figure 1 As shown, it is a schematic flowchart of the ecological method for controlling the pollution of early rainwater throughout the whole process provided by an embodiment of the present invention. In this embodiment, the ecological method for controlling the pollution of early rainwater throughout the whole process includes:

[0082] S1. Receive a control instruction, and confirm a pollution control environment based on the control instruction. Among them, the pollution control environment includes a target control area and a pollution control system, and the pollution control system includes: an area confirmation unit, a parameter confirmation unit, and a water quality detection unit.

[0083] It should be explained that the control instruction refers to an instruction used to control the pollution of early rainwater in the target control area. Generally, the control instruction is usually issued by a person or department that needs to control the pollution of early rainwater. The pollution control environment refers to the necessary environment for realizing the control of the pollution of early rainwater. The target control area refers to the area where the pollution of early rainwater needs to be controlled. The pollution control system refers to an APP or a small program that can recommend or retrieve corresponding control methods or parameters required during control in combination with the characteristics of the target control area, and the pollution control system includes an area confirmation unit, a parameter confirmation unit, and a water quality detection unit. For the specific application of the unit, please refer to the subsequent embodiments.

[0084] Exemplarily, Xiao Zhang is the person in charge of the environmental protection department. Now, Xiao Zhang needs to control the pollution of the initial rainwater in a designated area. Therefore, Xiao Zhang issues the control instruction, and Xiao Zhang identifies the target control area and the pollution control system. By conducting on-site inspections of the target control area, relevant characteristics of the target control area are obtained. Here, the relevant characteristics refer to the distribution of different pollutants. After inputting the relevant characteristics into the pollution control system, a sequence of ecological environment construction strategies recommended by the target control system in combination with the relevant characteristics is obtained. Among them, the sequence of ecological environment construction strategies includes multiple ecological environment construction strategies, and the ecological environment construction strategies include but are not limited to: the type and scale of LID facilities, the types, densities, and layouts of wetland plants, and the structures and materials of ecological revetments, the flow rate of initial rainwater discharge, and the retention time of initial rainwater at different locations. Xiao Zhang selects the target environment construction strategy from the sequence of ecological environment construction strategies in combination with the actual environment of the target control area and optimizes the target control area according to the target environment construction strategy. Here, the optimized target control area means that corresponding facilities are set or corresponding wetland plants are planted in the target control area. Whenever it rains in the optimized target control area, by detecting and predicting the characteristics of the rainfall, rainfall characteristics are obtained, and then the pollution control system can recommend or execute corresponding control methods in combination with the rainfall characteristics. Therefore, the main focus of the embodiments of the present invention is to combine the relevant characteristics of the target control area and the rainfall characteristics of the initial rainwater to improve the accuracy of pollution control of the initial rainwater.

[0085] It should be explained that LID facilities refer to a series of rainwater management measures based on the concept of low-impact development. LID facilities include but are not limited to: green roofs, rain gardens, and depressed green spaces. Wetland plants refer to plants growing in wetland environments. In the embodiments of the present invention, wetland plants mainly aim to purify the water quality of initial rainwater. An ecological revetment refers to an artificial waterfront revetment that restores the "permeability" of the natural riverbank. In the embodiments of the present invention, the ecological revetment mainly aims to purify the water quality of initial rainwater.

[0086] S2. Based on the area confirmation unit, multiple experimental simulation area groups are confirmed, where each experimental simulation area group includes multiple experimental simulation areas.

[0087] It should be explained that the confirmation of multiple experimental simulation area groups by the area confirmation unit includes:

[0088] Receiving and confirming the area confirmation instruction from the area confirmation unit, parsing the area confirmation instruction to obtain multiple initially designated areas, and performing the following operations on each of the multiple initially designated areas:

[0089] Divide the initial proposed area using a preset area division window to obtain a plurality of initial division areas, and perform the following operations on each of the plurality of initial division areas:

[0090] Identify the geometric center of the initial division area, obtain the reference coordinates of the geometric center, and use the reference coordinates to identify the initial division area to obtain an identified division area. Summarize the identified division areas to obtain a plurality of identified division areas, and the identified division areas correspond to the initial division areas one by one;

[0091] Count the number of initial division areas in the plurality of initial division areas to obtain an initial division quantity, calculate the product of a preset extraction density ratio and the initial division quantity to obtain a regional extraction quantity, and based on the regional extraction quantity and a pre-constructed uniform sampling algorithm, identify a plurality of target detection areas in the plurality of identified division areas;

[0092] Perform the following operations on each of the plurality of target detection areas:

[0093] Obtain a detection pollutant concentration group based on the target detection area, where the detection pollutant concentration group includes a plurality of pollutant concentrations marked with pollutant names;

[0094] Summarize the detection pollutant concentration groups to obtain a detection pollutant concentration group set, and obtain a plurality of experimental simulation area groups based on the detection pollutant concentration group set.

[0095] It should be understood that the initial proposed area refers to the area used for experiments. Here, the experiment refers to the area where the ecological environment construction strategy can be executed. For example: In order to test the actual effect of the ecological environment construction strategy, therefore, an area is planned where corresponding equipment can be installed or corresponding plants can be planted according to the ecological environment construction strategy, and the area where water quality detection is carried out is the initial proposed area. Generally, if there is an existing area with the same ecological environment construction strategy, the existing area can also be used as the target monitoring environment in the following embodiments.

[0096] Furthermore, the region division window refers to a region with a certain shape and area, which is used to divide the initially designated region, thereby improving the accuracy of analyzing different initially divided regions. For example, if the initially designated region is a 2×2 rectangular region and the region division window is a 1×1 rectangle, then the initially designated region can be divided into 4 initially divided regions through the region division window. Generally, the shape of the region division window can be set in combination with the shape of the initially designated region. After the shape and area of the region division window are confirmed, the geometric center of the initially divided region can be confirmed. For the convenience of understanding, taking a two-dimensional coordinate system as an example, for instance, if the initially divided region is a 1×1 rectangular region and the four vertices corresponding to this rectangular region are (0, 0), (1, 1), (1, 0), and (0, 1) respectively, then the geometric center corresponding to this initially divided region is confirmed to be (0.5, 0.5). Optionally, an image processing method can be used to obtain the geometric center of the initially divided region, and the same effect can be achieved by using other technologies, which will not be elaborated here. The reference coordinate refers to the coordinate used to represent the position of the geometric center. For example, if the reference coordinate is (1, 2, 3), using the reference coordinate to label the initially divided region can label the initially divided region as the (1, 2, 3)-initially divided region, where the (1, 2, 3)-initially divided region is the labeled divided region. The uniform sampling algorithm refers to an algorithm that can evenly extract multiple labeled divided regions from multiple labeled divided regions, and the extracted labeled divided regions are the target detection regions. Optionally, the uniform sampling algorithm is the Latin hypercube sampling method, and the same effect can be achieved by using other methods, which will not be elaborated here. The purpose of using the uniform sampling algorithm is to evenly select multiple target detection regions from multiple labeled divided regions to improve the accuracy of subsequent prediction of pollutants.

[0097] It can be understood that the pollutant concentration refers to the concentration of substances that can pollute water bodies. The pollutant name refers to the name used to represent the pollutant. Here, the pollutant name can be a specific name or the general name of a certain type of pollutant. For example, the pollutant name can be heavy metals or organophosphorus.

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

[0099] Summarize the pollutant concentrations in the detected pollutant concentration set by pollutant name respectively to obtain multiple analyzed pollutant concentration sets, and perform the following operations on each analyzed pollutant concentration set in the multiple analyzed pollutant concentration sets:

[0100] Identify multiple target prediction regions in the multiple labeled divided regions, and perform the following operations on each target prediction region in the multiple target prediction regions: [[ID=I3]]

[0101] Calculate the predicted pollutant concentration based on the target prediction area, the pre-constructed pollution prediction relational expression, and the analyzed pollutant concentration set, summarize the predicted pollutant concentration to obtain a predicted pollutant concentration group, and use the predicted pollutant concentration group to identify the target prediction area to obtain an identified prediction area;

[0102] Use the detected pollutant concentration group to identify the target detection area to obtain an identified detection area;

[0103] Summarize the identified detection area and the identified prediction area to obtain a target division area set, where the target division area set includes multiple target division areas, and the target division area is the identified detection area or the identified prediction area;

[0104] Extract a monitoring clustering data set from the target division area set, where the monitoring clustering data set includes multiple monitoring clustering data, and the monitoring clustering data corresponds to the target division area one by one, and the monitoring clustering data is as follows:

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

[0106] Wherein, C represents the monitoring clustering data, z represents the reference coordinate corresponding to the target division area, and N1, N2, N H respectively represent the first, second, and Hth predicted pollutant concentrations in the predicted pollutant concentration group corresponding to the target division area or the first, second, and Hth pollutant concentrations in the detected pollutant concentration group, and M represents that there are M predicted pollutant concentrations or pollutant concentrations in the predicted pollutant concentration group or the detected pollutant concentration group;

[0107] Obtain multiple experimental simulation area groups based on the monitoring clustering data set and the target division area set.

[0108] It can be understood that the pollutant concentrations of different pollutant names may be affected by the actual environment. Furthermore, summarizing the pollutant concentrations in the detected pollutant concentration group set by pollutant name can improve the accuracy of predicting specific pollutants in the target prediction area. The predicted pollutant concentration group refers to the set of pollutant concentrations obtained by predicting the concentrations of pollutants contained in the target prediction area using the analyzed pollutant concentration set, and the difference between the predicted pollutant concentration group and the detected pollutant concentration group is that the detected pollutant concentration group is obtained by on-site detection.

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

[0110]

[0111] Among them, J i represents the i-th pollutant concentration in the analysis of pollutant concentration concentration, and J max represents the preset reference pollutant concentration, and the reference pollutant concentration is related to the pollutant name corresponding to the i-th pollutant concentration. t represents the preset ratio threshold, p0 represents the preset weight value, {} represents rounding up, Y0 represents the predicted pollutant concentration corresponding to the target prediction area, n represents that there are n pollutant concentrations in the analysis of pollutant concentration concentration, and d(Y0, Y i ) represents the Euclidean distance between the reference coordinates corresponding to the target prediction area and the reference coordinates of the target detection area corresponding to the i-th pollutant concentration.

[0112] It should be explained that the reference pollutant concentration refers to the maximum value used to evaluate the pollution degree caused by the pollutant concentration, and the pollutant name corresponding to the reference pollutant concentration is the same as the pollutant name corresponding to the i-th pollutant concentration. Optionally, the reference pollutant concentration is obtained through the national soil pollution risk control standard. The same effect can be achieved by using other technologies, which will not be elaborated here. For example, now it is necessary to evaluate the concentration of heavy metals, that is, the i-th pollutant concentration is the concentration of heavy metals. Therefore, when obtaining the reference pollutant concentration, the threshold for limiting the concentration of heavy metals can be consulted from the national soil pollution risk control standard, and this threshold is used as the reference pollutant concentration.

[0113] Furthermore, when the ratio between the pollutant concentration and the reference pollutant concentration is large, here it means that the ratio is greater than the ratio threshold, which indicates that the pollutant concentration corresponding to the target detection area may have a greater impact on the surrounding target prediction area. Therefore, the embodiment of the present invention improves the accuracy of predicting the pollutant concentration in the target prediction area by dynamically adjusting the weight value.

[0114] Furthermore, obtaining multiple experimental simulation area groups based on the monitoring clustering data set and the target division area set includes:

[0115] Using the pollutant name, multiple analysis pollution concentration sets are extracted from the monitoring clustering data set. Among them, the analysis pollution concentration sets correspond one-to-one with the pollutant name, and each analysis pollution concentration set includes multiple analysis pollutant concentrations. The analysis pollutant concentration is the predicted pollutant concentration or the pollutant concentration, and the analysis pollutant concentration corresponds one-to-one with the initial division area;

[0116] The following operations are performed on each analysis pollution concentration set in the multiple analysis pollution concentration sets:

[0117] Obtain the pollution control threshold based on the pollutant name, and use the pollution control threshold to extract the pollution control concentration set from the analyzed pollution concentrations. Among them, 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] Count the number of pollution control concentrations in the pollution control concentration set to obtain the number of control regions, and calculate the ratio of the number of control regions to the initial division number to obtain the control region ratio;

[0119] If the control region ratio is greater than or equal to the preset control ratio threshold, update the monitoring clustering data set using the pollution control concentration set to obtain the updated monitoring clustering data set;

[0120] Otherwise, remove the analyzed pollution concentrations corresponding to the analyzed pollution concentration set from the monitoring clustering data set to obtain the updated monitoring clustering data set;

[0121] Obtain multiple experimental simulation region groups based on the updated monitoring clustering data set and the target division region set.

[0122] It should be noted that the analyzed pollution concentration set refers to the set of pollutant concentrations with the same pollutant name in the monitoring clustering data set. The pollution control threshold refers to the threshold used to determine whether the pollutant needs to be treated. The acquisition method of the pollution control threshold is the same as the acquisition method of the reference pollutant concentration, which will not be elaborated here. Generally, when the control region ratio is less than the control ratio threshold, it indicates that the pollutants corresponding to the pollutant name that need to be pollution-controlled in the initially proposed region may be caused by accidental factors. Updating the monitoring clustering data set using the pollution control concentration set means: according to the pollutant name, replacing the concentration of the pollutant corresponding in the monitoring clustering data set with the pollution control concentration set.

[0123] Exemplarily, the pollution control concentration set includes 3 pollution control concentrations, and the 3 pollution control concentrations correspond to the first three monitoring clustering data in the monitoring clustering data set. After updating the monitoring clustering data set using the pollution control concentration set, only the first three monitoring clustering data in the monitoring clustering data set include the pollution control concentration, and the remaining monitoring clustering data in the monitoring clustering data set do not include the monitoring clustering data.

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

[0125] Use the pre-constructed clustering algorithm to cluster the updated monitoring clustering data set to obtain multiple grouped data sets, and perform the following operations on each grouped data set in the multiple grouped data sets:

[0126] Using the grouped data set, a grouped division area set is identified in the target division area set;

[0127] Based on a preset governance area and the grouped division area set, a plurality of target fitting areas are obtained, wherein the area corresponding to each target fitting area is the governance area;

[0128] Based on a preset simulation classification value, a plurality of experimental simulation area groups are extracted from the plurality of target fitting areas, wherein each experimental simulation area group includes a plurality of experimental simulation areas, and the number of experimental simulation areas included in each experimental simulation area group is the simulation classification value.

[0129] Further, the clustering algorithm refers to an algorithm that can cluster the monitoring clustering data in the updated monitoring clustering data set. Optionally, the k-means clustering algorithm is used as the clustering algorithm. The same effect can be achieved by using other techniques, which will not be elaborated here. The grouped data set refers to the data set obtained after clustering the updated monitoring clustering data set by using the clustering algorithm. For example, if the updated monitoring clustering data set is clustered into 5 clusters by using the k-means clustering algorithm, the monitoring clustering data included in each of the 5 clusters constitutes the grouped data set.

[0130] It should be explained that the grouped division area set is a set of areas identified in the target division area set by the grouped data set. Generally, the grouped data set includes a plurality of monitoring clustering data, and the monitoring clustering data corresponds one-to-one with the target division areas in the target division area set. Therefore, the grouped division area set can be identified in the target division area set through the correspondence between the grouped data in the grouped data set and the target division areas in the target division area set.

[0131] It should be understood that the grouped partitioning regions identified using the grouped data set may not be adjacent, and for non - adjacent regions, when conducting pollution control assessment subsequently, the results of the pollution control assessment may be affected by the remaining regions. Furthermore, there may be a problem of inaccurate assessment results when conducting pollution control assessment for such regions. Here, the region refers to the target fitting region. Therefore, the embodiments of the present invention require the area corresponding to the target fitting region to be the treatment area. Thus, while improving the practicality of the embodiments of the present invention, the accuracy of subsequent pollution control assessment for the target fitting region is improved. For ease of understanding, here, taking a two - dimensional coordinate system as an example, where each square region with a side length of 1 is the initial partitioning region. The grouped partitioning region set includes: 4 initial partitioning regions, and the 4 initial partitioning regions are respectively composed of 3 pairwise - adjacent square regions and an independent square region. The preset treatment area is 2, then a target fitting region can be obtained using the treatment area and the grouped partitioning region set. Among them, the obtained target fitting region includes 2 square regions, and the 2 square regions are the regions corresponding to two adjacent squares.

[0132] S3. Confirm the receipt of the parameter confirmation instruction from the parameter confirmation unit, parse the parameter confirmation instruction to obtain a set of regulation parameters. Among them, the set of regulation parameters includes multiple regulation parameter ranges. Based on the set of regulation parameters, obtain multiple first fitting parameter groups, and in a combined manner, use the multiple first fitting parameter groups and multiple experimental simulation region groups to obtain multiple matching nodes.

[0133] Furthermore, the regulation parameter range refers to the range that can adjust the parameters in the ecological environment construction strategy, and this range is related to the facilities in the ecological environment construction strategy. For example, the facility in the ecological environment construction strategy is a certain wetland plant, and the parameter that can be adjusted is the density of the wetland plant. Here, the regulation parameter range refers to the range of the density of the wetland plant during planting. Generally, the facilities that can be arranged in the ecological environment construction strategy can be obtained through the empirical method. When the ecological environment construction strategy is confirmed, the regulation parameter range can be confirmed.

[0134] It should be explained that the obtaining of multiple first fitting parameter groups based on the set of regulation parameters includes:

[0135] Perform the following operations on each regulation parameter range in the set of regulation parameters:

[0136] Use the preset sampling value to perform uniform sampling within the regulation parameter range to obtain a sampled regulation parameter group. Among them, the sampled regulation parameter group includes multiple sampled regulation parameters, and the number of sampled regulation parameters corresponds to the sampling value;

[0137] Summarize the set of sampling control parameter groups to obtain a set of sampling control parameter groups. In a combined manner, use the set of sampling control parameter groups to obtain multiple first fitting parameter groups, where each first fitting parameter group includes multiple sampling control parameters, and the sampling control parameters correspond one-to-one with the control parameter ranges.

[0138] Exemplarily, the sampling value is 5, and the control parameter range is from 0 to 10. Using uniform sampling, the following 5 sampling control parameters can be sampled from the control parameter range: 1, 3, 5, 7, and 9. These 5 sampling control parameters form the sampling control parameter group.

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

[0140] It should be explained that constructing a target monitoring environment based on the matching nodes means: according to the sampling control parameters corresponding to the first fitting parameter group in the matching nodes, construct 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: use green roofs in all LID facilities, the type of wetland plants is cattail, and the planting density of wetland plants is 55 plants per square meter. Then, use the ecological environment construction strategy to lay green roofs in the experimental simulation area and plant cattail at a density of 55 plants per square meter in the wetland environment for water purification.

[0141] S5. Obtain target monitoring parameters based on the target monitoring environment, where the target monitoring parameters include reference rainfall time, reference rainfall pattern, and reference rainfall intensity. Use the target monitoring environment and the water quality detection unit to obtain a reference decontamination evaluation value.

[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 when the current rainfall is monitored. Generally, the embodiments of the present invention obtain the data required for subsequent embodiments through experiments in the actual environment, and the main purpose of the embodiments of the present invention is to improve the accuracy of pollution control for initial rainwater. It is not difficult to understand that the premise for obtaining the reference decontamination evaluation value is that there is rainfall in the target monitoring environment. Here, the rainfall is the current rainfall. The reference rainfall pattern refers to the time distribution characteristics of the rainfall intensity during the current rainfall. The reference rainfall intensity refers to the rainfall amount per unit time. In the embodiments of the present invention, the target monitoring parameters all refer to the parameters corresponding to the initial rainwater. Optionally, the reference rainfall pattern can be obtained through radar observation technology, and the technology for obtaining the reference rainfall pattern is an existing technology and will not be elaborated here. The reference rainfall time can be obtained through statistical methods.

[0143] It can be understood that the obtaining of the reference decontamination evaluation value using the target monitoring environment and the water quality detection unit includes:

[0144] Identify a set of target detection pollutants using the target monitoring environment. The set of target detection pollutants includes multiple target detection pollutants. Obtain multiple sets of purified pollutant concentrations based on the water quality detection unit, the set of target detection pollutants, and the target monitoring environment. Each set of purified pollutant concentrations corresponds one-to-one to a target detection pollutant, and each set of purified pollutant concentrations includes multiple purified pollutant concentrations. Each purified pollutant concentration corresponds one-to-one to a target fitting area corresponding to the target monitoring environment.

[0145] Score the target detection pollutants in the set of target detection pollutants to obtain a set of pollutant score values, where the set of pollutant score values includes multiple pollutant score values.

[0146] Perform the following operations on each set of purified pollutant concentrations in the multiple sets of purified pollutant concentrations:

[0147] Obtain the variance of the purified pollutant concentrations based on the set of purified pollutant concentrations, where the variance of the purified pollutant concentrations is the variance of the multiple purified pollutant concentrations in the set of purified pollutant concentrations.

[0148] Compare the variance of the purified pollutant concentrations with a preset concentration variance threshold. After confirming that the variance of the purified pollutant concentrations is less than or equal to the concentration variance threshold, calculate a reference decontamination evaluation value using the set of pollutant score values and the multiple sets of purified pollutant concentrations.

[0149] Furthermore, the set of target detection pollutants refers to the set of pollutant names updated in the monitoring clustering dataset. The water quality detection unit refers to a unit or technology capable of detecting the pollutant content in the initial rainwater. Optionally, the near-infrared spectroscopy technology is used to detect the concentration of pollutants in the initial rainwater, and the same effect can be achieved using other technologies, which will not be elaborated here. The purpose of scoring the target detection pollutants is to distinguish the impact of different pollutants on the environment. Optionally, the 1-9 scale method is used to score the target detection pollutants, and it should be clear that in the embodiments of the present invention, the larger the pollutant score value, the higher the impact of the pollutant on the environment. The variance of the purified pollutant concentrations being less than or equal to the concentration variance threshold indicates that there is no accidental phenomenon, and thus, the accuracy of calculating the reference decontamination evaluation value can be improved.

[0150] It should be understood that calculating the reference decontamination evaluation value using the set of pollutant score values and the multiple sets of purified pollutant concentrations includes:

[0151] Obtain multiple average values of purified pollutant concentrations based on the multiple sets of purified pollutant concentrations, and identify multiple initial pollutant concentration average values using the target monitoring environment, where each initial pollutant concentration average value corresponds one-to-one to the average value of the purified pollutant concentration.

[0152] Calculate the reference decontamination evaluation value using multiple mean values of purified pollutant concentrations, multiple mean values of initial pollutant concentrations, and a set of pollutant score values. The calculation formula is as follows:

[0153]

[0154] Where P represents the reference decontamination evaluation value, b represents that there are b pollutant score values in the set of pollutant score values, q a and q w represent the a-th and w-th pollutant score values in the set of pollutant score values respectively, g w represents the mean value of the initial pollutant concentration corresponding to the w-th pollutant score value among the multiple mean values of the initial pollutant concentrations, and f w represents the mean value of the purified pollutant concentration corresponding to the w-th pollutant score value among the multiple mean values of the purified pollutant concentrations.

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

[0156] S6. Confirm the target decontamination fitting parameter database based on the reference decontamination evaluation value and the target monitoring parameters. Among them, 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.

[0157] It should be explained that the confirmation of the target decontamination fitting parameter database based on the reference decontamination evaluation value and the target monitoring parameters includes:

[0158] Extract the reference pollutant mean value set from the updated monitoring clustering dataset using the pollutant name. The reference pollutant mean value set includes multiple target pollutant mean values;

[0159] Associate the reference decontamination evaluation value, the first fitting parameter group, and the reference pollutant mean value set to obtain fitting data;

[0160] Summarize the fitting data to obtain a fitting dataset;

[0161] Use the fitting dataset to construct a decontamination evaluation surface with the reference decontamination evaluation value as the dependent variable, and summarize the decontamination evaluation surface to obtain the target decontamination fitting parameter database.

[0162] It is understandable that the target pollutant mean value refers to the mean value of the pollutant concentrations corresponding to each pollutant name in the updated monitoring clustering dataset. Optionally, through polynomial regression, a decontamination evaluation surface is constructed with the reference decontamination evaluation value in the fitting data as the dependent variable and the remaining parameters in the fitting data as the independent variables.

[0163] Furthermore, the target decontamination fitting parameter data refers to the parameters corresponding to each decontamination evaluation surface in the target decontamination fitting parameter database. Among them, the reference area monitoring parameter refers to the reference pollutant mean value 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, and based on the target area monitoring parameters and reference monitoring parameters, retrieve the target control parameters in the target decontamination fitting parameter database to achieve the control of the initial rainwater pollution 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 elaborated here. The definitions of the reference monitoring parameters and the target monitoring parameters are the same and will not be elaborated here. The difference between the reference monitoring parameters and the target monitoring parameters is that the reference monitoring parameters are the parameters used to characterize the rain type, and this parameter is a predicted value. Optionally, the parameters used to characterize the rain type in the reference monitoring parameters are obtained through a pre-trained neural network model. The same effect can be achieved by using other technologies and will not be elaborated here. Generally, when the target area monitoring parameters and reference monitoring parameters do not exist in the target decontamination fitting parameter database, the decontamination evaluation surface corresponding to the parameters that are close 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 this decontamination evaluation surface. The close 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 evaluation surface, and taking the parameters corresponding to the smallest Euclidean distance as the close parameters. Similarly, the number of decontamination evaluation surfaces in the target decontamination fitting parameter database can also be supplemented through existing technologies to enrich the target decontamination fitting parameter database. Optionally, after constructing the relationship between the dependent variable and the independent variable through parametric modeling, by changing the value of the independent variable, different decontamination evaluation surfaces are obtained. The same effect can be achieved by using other technologies and will not be elaborated here.

[0166] Furthermore, after the target area monitoring parameters and reference monitoring parameters are confirmed, the corresponding decontamination evaluation surface can be retrieved in the target decontamination fitting parameter database through the target area monitoring parameters and reference monitoring parameters, and the first fitting parameter group corresponding to the largest reference decontamination evaluation value can be identified in the confirmed decontamination evaluation surface to obtain the target control parameters for controlling the pollution of the initial rainwater.

[0167] Compared with the problems described in the background art, the present invention identifies multiple experimental simulation area groups based on the area confirmation unit. It can be seen that the embodiments of the present invention consider the characteristics of the experimental simulation area groups when identifying the experimental simulation area groups, so that the areas corresponding to the identified experimental simulation area groups meet the credibility while excluding accidental factors. Therefore, the target monitoring environment constructed using the experimental simulation area groups lays a foundation for the accuracy of the subsequent obtained reference decontamination evaluation values. When identifying the experimental simulation area groups, the concentrations of pollutants in different initially divided areas are also considered, and different relational expressions for calculating the predicted pollutant concentration are formulated in combination with the pollutant concentrations, making the calculated predicted pollutant concentration more accurate. When identifying the experimental simulation area groups, the feasibility of the experimental simulation area groups is also considered. Here, the feasibility means that the areas of the target fitting areas corresponding to the experimental simulation area groups are all the treatment areas. The present invention obtains target monitoring parameters based on the target monitoring environment, where the target monitoring parameters include the reference rainfall time, reference rainfall pattern, and reference rainfall intensity. The reference decontamination evaluation value is obtained using the target monitoring environment and the water quality detection unit, and the target decontamination fitting parameter database is identified based on the reference decontamination evaluation value and the target monitoring parameters. It can be seen that the present invention not only considers the pollution situation of the geology corresponding to the simulation experiment area groups, but also considers the rainfall characteristics corresponding to the initial rainwater. Here, the rainfall characteristics refer to the target monitoring parameters. Furthermore, the target decontamination fitting parameter database can improve the intelligence and accuracy of the initial rainwater pollution control for different areas by comprehensively considering the rainfall characteristics, pollution situation, and characteristics of different control schemes. Therefore, the ecological whole-process initial rainwater pollution control method, device, electronic device, and computer-readable storage medium proposed by the present invention mainly aim to improve the accuracy of the pollution control of the initial rainwater.

[0168] Embodiment 2:

[0169] As Figure 2 shown, it is a schematic structural diagram of an electronic device for implementing the ecological whole-process initial rainwater pollution control method provided by 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 operable on the processor 10, such as the ecological whole-process initial rainwater pollution control program.

[0171] Among them, the memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (such as SD or DX memory, etc.), magnetic memory, magnetic disk, optical disc, etc. In some embodiments, the memory 11 may be an internal storage unit of the electronic device 1, such as the mobile hard disk of the electronic device 1. In some other embodiments, the memory 11 may also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. equipped on the electronic device 1. Further, the memory 11 may also include both the internal storage unit and the external storage device of the electronic device 1. The memory 11 can be used not only to store application software installed on the electronic device 1 and various types of data, such as the code of the whole-process initial rainwater pollution control program of the ecosystem, etc., but also to temporarily store the data that has been output or will be output.

[0172] In some embodiments, the processor 10 may be composed of integrated circuits. For example, it may be composed of a single packaged integrated circuit, or may be composed of multiple integrated circuits with the same or different functions, including the combination of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips, etc. The processor 10 is the control core (Control Unit) of the electronic device, connecting various components of the whole electronic device through various interfaces and lines, and by running or executing the programs or modules stored in the memory 11 (such as the whole-process initial rainwater pollution control program of the ecosystem, etc.), and calling the data stored in the memory 11, to execute various functions of the electronic device 1 and process data.

[0173] The bus may 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 set to realize the connection and communication between the memory 11 and at least one processor 10, etc.

[0174] Figure 2 Only the electronic device with components is shown. Those skilled in the art can understand that, Figure 2The structure shown does not constitute a limitation on the electronic device 1, and it may include fewer or more components than those shown, or combine certain components, or have different component arrangements.

[0175] For example, although not shown, the electronic device 1 may further include a power source (such as a battery) for supplying power to each component. Preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so as to implement functions such as charging management, discharging management, and power consumption management through the power management device. The power source may also include any components such as one or more DC or AC power sources, a recharge device, a power failure detection circuit, a power converter or inverter, and a power status indicator. The electronic device 1 may also include various sensors, a Bluetooth module, a Wi-Fi module, etc., which will not be elaborated here.

[0176] Furthermore, the electronic device 1 may further 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 generally used to establish a communication connection between the electronic device 1 and other electronic devices.

[0177] Optionally, the electronic device 1 may further include a user interface. The user interface may be a display, an input unit (such as a keyboard), and optionally, the user interface may also be a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch liquid crystal display, and an OLED (Organic Light-Emitting Diode) toucher, etc. Among them, the display may also be appropriately referred to as a display screen or a display unit, which is used to display the information processed in the electronic device 1 and to display a visual user interface.

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

[0179] The whole-process initial rainwater pollution control program stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can implement:

[0180] Receive a control instruction, and confirm a pollution control environment based on the control instruction. Among them, the pollution control environment includes a target control area and a pollution control system, and the pollution control system includes: an area confirmation unit, a parameter confirmation unit, and a water quality detection unit;

[0181] Based on the area confirmation unit, confirm multiple experimental simulation area groups, where each experimental simulation area group includes multiple experimental simulation areas;

[0182] It receives and confirms a parameter confirmation instruction from a parameter confirmation unit, parses the parameter confirmation instruction to obtain a set of regulation parameters, where the set of regulation parameters includes multiple regulation parameter ranges, obtains multiple first fitting parameter groups based on the set of regulation parameters, and in a combined manner, uses the multiple first fitting parameter groups and multiple experimental simulation area groups to obtain multiple matching nodes, where a matching node includes a first fitting parameter group and an experimental simulation area group;

[0183] Perform the following operations on each of the multiple matching nodes:

[0184] Construct a target monitoring environment based on the matching node;

[0185] Obtain target monitoring parameters based on the target monitoring environment, where the target monitoring parameters include reference rainfall time, reference rainfall pattern, and reference rainfall intensity, and use the target monitoring environment and a water quality detection unit to obtain a reference decontamination evaluation value;

[0186] Confirm a target decontamination fitting parameter database based on the reference decontamination evaluation value and the target monitoring parameters, where 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, a target fitting parameter group, and target monitoring parameters;

[0187] Obtain target area monitoring parameters and reference monitoring parameters of a target control area, and retrieve target control parameters from the target decontamination fitting parameter database based on the target area monitoring parameters and the reference monitoring parameters to achieve the control of the initial rainwater pollution in the target control area.

[0188] Specifically, the specific implementation method of the above instructions by the processor 10 can refer to Figures 1 to 2 the description of the relevant steps in the corresponding embodiment, which will not be elaborated here.

[0189] Furthermore, if the modules / units integrated in the electronic device 1 are implemented in the form of software function 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 can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disc, a computer memory, a read-only memory (ROM, Read-Only Memory).

[0190] The present invention also provides a computer-readable storage medium, where the readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, it can implement:

[0191] Receive a control instruction, and confirm a pollution control environment based on the control instruction. Among them, the pollution control environment includes a target control area and a pollution control system, and the pollution control system includes: an area confirmation unit, a parameter confirmation unit, and a water quality detection unit;

[0192] Based on the area confirmation unit, confirm multiple groups of experimental simulation areas. Among them, each group of experimental simulation areas includes multiple experimental simulation areas;

[0193] Confirm to receive a parameter confirmation instruction from the parameter confirmation unit, parse the parameter confirmation instruction to obtain a set of regulation parameters. Among them, the set of regulation parameters includes multiple ranges of regulation parameters. Based on the set of regulation parameters, obtain multiple groups of first fitting parameters. In a combined manner, use the multiple groups of first fitting parameters and the multiple groups of experimental simulation areas to obtain multiple matching nodes. Among them, each matching node includes a group of first fitting parameters and a group of experimental simulation areas;

[0194] Perform the following operations on each of the multiple matching nodes:

[0195] Construct a target monitoring environment based on the matching node;

[0196] Obtain target monitoring parameters based on the target monitoring environment. Among them, the target monitoring parameters include reference rainfall time, reference rainfall pattern, and reference rainfall intensity. Use the target monitoring environment and the water quality detection unit to obtain a reference decontamination evaluation value;

[0197] Based on the reference decontamination evaluation value and the target monitoring parameters, confirm a target decontamination fitting parameter database. Among them, 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, a target fitting parameter group, and target monitoring parameters;

[0198] Obtain the target area monitoring parameters and reference monitoring parameters of the target control area. Based on the target area monitoring parameters and the reference monitoring parameters, retrieve the target control parameters in the target decontamination fitting parameter database to achieve the initial rainwater pollution control of the target control area.

[0199] The module described as a separate component may or may not be physically separated. The component shown as a module may or may not be a physical unit, that is, it may be located in one place, or it may be distributed to multiple network units. You can select some or all of the modules according to actual needs to achieve the purpose of the solution of this embodiment.

[0200] In addition, in each embodiment of the present invention, each functional module can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated unit can be implemented in the form of hardware, or in the form of a combination of hardware and software functional modules.

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

[0202] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An ecological method for controlling the pollution of initial rainwater in the whole process, characterized in that, The method includes: Receiving a control instruction, and confirming a pollution control environment based on the control instruction. The pollution control environment includes a target control area and a pollution control system, and the pollution control system includes: an area confirmation unit, a parameter confirmation unit, and a water quality detection unit; Confirming multiple experimental simulation area groups based on the area confirmation unit, where each experimental simulation area group includes multiple experimental simulation areas; Confirming to receive a parameter confirmation instruction from the parameter confirmation unit, parsing the parameter confirmation instruction to obtain a set of regulation parameters. The set of regulation parameters includes multiple regulation parameter ranges. Based on the set of regulation parameters, obtaining multiple first fitting parameter groups, and in a combined manner, using the multiple first fitting parameter groups and the multiple experimental simulation area groups to obtain multiple matching nodes, where each matching node includes a first fitting parameter group and an experimental simulation area group; Performing the following operations on each of the multiple matching nodes: Constructing a target monitoring environment based on the matching node; Obtaining target monitoring parameters based on the target monitoring environment, where the target monitoring parameters include a reference rainfall time, a reference rainfall pattern, and a reference rainfall intensity, and using the target monitoring environment and the water quality detection unit to obtain a reference decontamination evaluation value; Confirming a target decontamination fitting parameter database based on the reference decontamination evaluation value and the target monitoring parameters. 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, a target fitting parameter group, and target monitoring parameters; Obtaining target area monitoring parameters and reference monitoring parameters of the target control area, and based on the target area monitoring parameters and the reference monitoring parameters, retrieving target control parameters in the target decontamination fitting parameter database to implement the initial rainwater pollution control of the target control area.

2. The initial rainwater pollution control method for the whole process of the ecosystem according to claim 1, characterized in that, The step of confirming multiple experimental simulation area groups based on the area confirmation unit includes: Confirming to receive an area confirmation instruction from the area confirmation unit, parsing the area confirmation instruction to obtain multiple initially designated areas, and performing the following operations on each of the multiple initially designated areas: Dividing the initially designated area using a preset area division window to obtain multiple initially divided areas, and performing the following operations on each of the multiple initially divided areas: Confirming the geometric center of the initially divided area, obtaining the reference coordinates of the geometric center, and using the reference coordinates to identify the initially divided area to obtain an identified divided area. Summarizing the identified divided areas to obtain multiple identified divided areas, and the identified divided areas correspond one-to-one to the initially divided areas; Counting the number of initially divided areas among the multiple initially divided areas to obtain an initial division number, calculating the product of a preset extraction density ratio and the initial division number to obtain an area extraction number, and based on the area extraction number and a pre-constructed uniform sampling algorithm, confirming multiple target detection areas among the multiple identified divided areas; Performing the following operations on each of the multiple target detection areas: Obtain a set of detected pollutant concentrations based on the target detection area, where the set of detected pollutant concentrations includes multiple pollutant concentrations marked with pollutant names; Summarize the set of detected pollutant concentrations to obtain a set of detected pollutant concentration groups, and obtain multiple experimental simulation area groups based on the set of detected pollutant concentration groups.

3. The ecological initial rainwater pollution control method according to claim 2, characterized in that, The obtaining of multiple experimental simulation area groups based on the set of detected pollutant concentration groups includes: Summarize the pollutant concentrations in the set of detected pollutant concentration groups using the pollutant names respectively to obtain multiple sets of analyzed pollutant concentrations, and perform the following operations on each set of analyzed pollutant concentrations in the multiple sets of analyzed pollutant concentrations: Identify multiple target prediction areas among the multiple marked division areas, and perform the following operations on each target prediction area among the multiple target prediction areas: Calculate the predicted pollutant concentration based on the target prediction area, the pre-constructed pollution prediction relationship formula, and the set of analyzed pollutant concentrations, summarize the predicted pollutant concentrations to obtain a set of predicted pollutant concentrations, and use the set of predicted pollutant concentrations to mark the target prediction area to obtain a marked prediction area; Use the set of detected pollutant concentrations to mark the target detection area to obtain a marked detection area; Summarize the marked detection area and the marked prediction area to obtain a set of target division areas, where the set of target division areas includes multiple target division areas, and the target division area is the marked detection area or the marked prediction area; Extract a monitoring clustering data set from the set of target division areas, where the monitoring clustering data set includes multiple monitoring clustering data, and the monitoring clustering data corresponds one-to-one with the target division area, and the monitoring clustering data is as follows: C = (z, N1, N2, …, N H , …, N M ) Among them, C represents the monitored clustering data, z represents the reference coordinates corresponding to the target division area, N1, N2, N H respectively represent the first, second, and Hth predicted pollutant concentrations in the predicted pollutant concentration group corresponding to the target division area or the first, second, and Hth pollutant concentrations in the detected pollutant concentration group, and M represents that there are M predicted pollutant concentrations or pollutant concentrations in the predicted pollutant concentration group or the detected pollutant concentration group; Obtain multiple experimental simulation area groups based on the monitoring clustering data set and the set of target division areas.

4. The method for controlling the pollution of initial rainwater in the whole process of the ecological environment according to claim 3, characterized in that, The pollution prediction relationship formula is as follows: Among them, J i represents the concentration of the i-th pollutant in the analysis of pollutant concentration concentration, and J max represents the preset reference pollutant concentration, and the reference pollutant concentration is related to the name of the pollutant corresponding to the i-th pollutant concentration. t represents the preset proportional threshold, p0 represents the preset weight value, {} represents rounding up, Y0 represents the predicted pollutant concentration corresponding to the target prediction area, n represents that there are n pollutant concentrations in the analysis of pollutant concentration concentration, and d(Y0, Y i ) represents the Euclidean distance between the reference coordinates corresponding to the target prediction area and the reference coordinates of the target detection area corresponding to the i-th pollutant concentration.

5. The ecological whole-process initial rainwater pollution control method according to claim 4, wherein The obtaining of multiple experimental simulation area groups based on the monitoring clustering data set and the set of target division areas includes: Use the pollutant names to extract multiple sets of analyzed pollution concentrations from the monitoring clustering data set, where the sets of analyzed pollution concentrations correspond one-to-one with the pollutant names, and each set of analyzed pollution concentrations includes multiple analyzed pollutant concentrations, and the analyzed pollutant concentrations are predicted pollutant concentrations or pollutant concentrations, and the analyzed pollutant concentrations correspond one-to-one with the initial division areas; Perform the following operations on each set of analyzed pollution concentrations in the multiple sets of analyzed pollution concentrations: Obtain a pollution control threshold based on the pollutant name, and use the pollution control threshold to extract a set of controlled pollution concentrations from the set of analyzed pollution concentrations, where the set of controlled pollution concentrations includes multiple controlled pollution concentrations, and the controlled pollution concentrations are greater than or equal to the pollution control threshold; Count the number of controlled pollution concentrations in the set of controlled pollution concentrations to obtain the number of controlled areas, and calculate the ratio of the number of controlled areas to the initial division number to obtain the controlled area ratio; If the controlled area ratio is greater than or equal to a preset controlled ratio threshold, then update the monitoring clustering data set using the set of controlled pollution concentrations to obtain an updated monitoring clustering data set; Otherwise, remove the analysis pollution concentrations corresponding to the analysis pollution concentration set from the monitoring clustering dataset to obtain an updated monitoring clustering dataset; Obtain multiple experimental simulation region groups based on the updated monitoring clustering dataset and the target division region set.

6. The ecological initial rainwater pollution control method in the whole process as described in claim 5, characterized in that, The obtaining of multiple experimental simulation region groups based on the updated monitoring clustering dataset and the target division region set includes: Use a pre-constructed clustering algorithm to cluster the updated monitoring clustering dataset to obtain multiple grouped datasets, and perform the following operations on each of the multiple grouped datasets: Use the grouped dataset to identify a grouped division region set in the target division region set; Obtain multiple target fitting regions based on a preset treatment area and the grouped division region set, where the areas corresponding to the target fitting regions are all the treatment area; Extract multiple experimental simulation region groups from the multiple target fitting regions based on a preset simulation classification value, where each experimental simulation region group includes multiple experimental simulation regions, and the number of experimental simulation regions included in the experimental simulation region group is the simulation classification value.

7. The ecological whole-process initial rainwater pollution control method according to claim 6, characterized in that The obtaining of multiple first fitting parameter groups based on the regulation parameter set includes: Perform the following operations on each regulation parameter range in the regulation parameter set: Use a preset sampling value to perform uniform sampling in the regulation parameter range to obtain a sampled regulation parameter group, where the sampled regulation parameter group includes multiple sampled regulation parameters, and the number of sampled regulation parameters corresponds to the sampling value; Summarize the sampled regulation parameter groups to obtain a set of sampled regulation parameter groups, and in a combined manner, use the set of sampled regulation parameter groups to obtain multiple first fitting parameter groups, where each first fitting parameter group includes multiple sampled regulation parameters, and the sampled regulation parameters correspond one-to-one with the regulation parameter range.

8. The method for controlling the pollution of initial rainwater in the whole process of the ecological environment according to claim 7, characterized in that The obtaining of the reference decontamination evaluation value using the target monitoring environment and the water quality detection unit includes: Use the target monitoring environment to identify a target detection pollutant set, where the target detection pollutant set includes multiple target detection pollutants, and obtain multiple purified pollutant concentration groups based on the water quality detection unit, the target detection pollutant set, and the target monitoring environment, where the purified pollutant concentration groups correspond one-to-one with the target detection pollutants, and each purified pollutant concentration group includes multiple purified pollutant concentrations, and the purified pollutant concentrations correspond one-to-one with the target fitting regions corresponding to the target monitoring environment; Score the target detection pollutants in the target detection pollutant set to obtain a pollutant score value set, where the pollutant score value set includes multiple pollutant score values; Perform the following operations on each purified pollutant concentration group in the multiple purified pollutant concentration groups: Obtain the variance of the purified pollutant concentrations based on the purified pollutant concentration group, where the variance of the purified pollutant concentrations is the variance of the multiple purified pollutant concentrations in the purified pollutant concentration group; Compare the variance of the purified pollutant concentrations with a preset concentration variance threshold, and after confirming that the variance of the purified pollutant concentrations is less than or equal to the concentration variance threshold, calculate the reference decontamination evaluation value using the pollutant score value set and the multiple purified pollutant concentration groups.

9. The initial rainwater pollution control method for the whole process of the ecosystem according to claim 8, characterized in that, Calculating a reference decontamination evaluation value by using a pollutant score value set and multiple purified pollutant concentration groups, including: Obtaining multiple purified pollutant concentration means based on the multiple purified pollutant concentration groups, and using a target monitoring environment to confirm multiple initial pollutant concentration means, where the initial pollutant concentration means and the purified pollutant concentration means correspond one by one; Calculating a reference decontamination evaluation value by using the multiple purified pollutant concentration means, the multiple initial pollutant concentration means and the pollutant score value set, and the calculation formula is as follows: Wherein, P represents the reference decontamination evaluation value, b represents that there are b pollutant score values in the pollutant score value set, q a , q w respectively represent the a-th and w-th pollutant score values in the pollutant score value set, g w represents the initial pollutant concentration mean corresponding to the w-th pollutant score value among multiple initial pollutant concentration means, f w represents the purified pollutant concentration mean corresponding to the w-th pollutant score value among multiple purified pollutant concentration means.

10. The initial rainwater pollution control method for the whole process of the ecosystem according to claim 9, characterized in that, Confirming a target decontamination fitting parameter database based on the reference decontamination evaluation value and target monitoring parameters, including: Extracting a reference pollutant mean set from the updated monitoring clustering dataset by using the pollutant names, where the reference pollutant mean set includes multiple target pollutant means; Associating the reference decontamination evaluation value, the first fitting parameter group and the reference pollutant mean set to obtain fitting data; Summarizing the fitting data to obtain a fitting dataset; Taking the reference decontamination evaluation value as the dependent variable, constructing a decontamination evaluation surface by using the fitting dataset, and summarizing the decontamination evaluation surface to obtain a target decontamination fitting parameter database.

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