Method and device for evaluating influence degree of industrial production on river environment

Abstract

The invention relates to a method and device for evaluating the influence degree of industrial production on the river environment, and belongs to the technical field of clean production, and the method comprises the steps: obtaining target water quality data of a plurality of monitoring points in a target river in a plurality of time periods, and employing a fuzzy clustering mode based on a plurality of water quality categories, each data in the target water quality data corresponding to each monitoring point is processed to determine the water quality category of the water area where each monitoring point is located in each time period, and according to the water quality change conditions of the water area where each monitoring point is located in multiple time periods, the water quality category of the water area where each monitoring point is located in multiple time periods is determined; according to the method, the accuracy of the evaluation result is improved, and business guidance is conveniently provided for the enterprises to optimize the production mode.

Description

Technical Field

[0001] The present application relates to the field of clean production technology, and in particular to a method and device for evaluating the impact of industrial production on river environment. Background Art

[0002] In recent years, with the rapid development of various industrial technologies, the impact of industrial production on the environment has become an issue of increasing concern. Among them, rivers are the main source of water for humans, and the quality of their river environment is particularly important to people. By studying the impact of industrial production on the river environment, it can help companies optimize their own industrial production methods.

[0003] In related technologies, the water quality index (WQI) (an index used to evaluate the quality of water bodies, which integrates the indicators of multiple water quality parameters) is usually used to reflect the overall pollution level of water bodies, and then evaluate the impact of industrial production on the river environment. For example, based on the various water quality parameters collected at the river monitoring points, the WQI is calculated to obtain the WQI score. The higher the score, the worse the water quality, indicating that the industrial production near the monitoring point has a greater impact on the river environment.

[0004] However, in the above methods, water quality parameters are often pH value, dissolved oxygen, conductivity, etc. These parameters have no direct relationship with the pollution sources generated by industrial production, resulting in poor accuracy of the final evaluation results. Summary of the invention

[0005] This application provides a method and device for evaluating the impact of industrial production on river environment, which can accurately and quickly evaluate the environmental impact of industrial production enterprises on target river areas. The technical solution of this application is as follows:

[0006] In the first aspect, the present application provides a method for evaluating the impact of industrial production on river environment, the method comprising:

[0007] Obtain target water quality data at multiple monitoring points in a target river area in multiple time periods, where at least one industrial production enterprise is deployed in the land area corresponding to each monitoring point, and the target water quality data indicates the content of at least one metal in the water area where the corresponding monitoring point is located;

[0008] Based on multiple water quality categories, each data in the target water quality data corresponding to each monitoring point is standardized to obtain a dimensionless value of each data in the target water quality data corresponding to each monitoring point, wherein the water quality category is used to indicate the pollution status of the water area;

[0009] Based on the multiple water quality categories and the dimensionless value of each data in the target water quality data corresponding to each monitoring point, determining a cluster reference function for each evaluation parameter in the target water quality data, wherein the cluster reference function is used to indicate the water quality category to which the data monitored under the corresponding evaluation parameter belongs;

[0010] Based on the dimensionless value of each data in the target water quality data corresponding to each monitoring point, the clustering reference function of each evaluation parameter in the target water quality data, and the clustering weight, a plurality of clustering coefficients of each monitoring point in each time period are determined, one clustering coefficient corresponds to one water quality category, and the clustering coefficient indicates the probability that the water area where the corresponding monitoring point is located belongs to any water quality category in each time period;

[0011] Based on multiple clustering coefficients of each monitoring point in each time period, determine the water quality category of the water area where each monitoring point is located in each time period;

[0012] Based on the water quality category of the water area where each monitoring point is located in each time period, determine the water quality change information of the water area where each monitoring point is located in the multiple time periods, and the water quality change information indicates the pollution change of the water area where the corresponding monitoring point is located in the multiple time periods;

[0013] Based on the water quality change information of the water area where each monitoring point is located during the multiple time periods, the environmental impact assessment results of the industrial production enterprises corresponding to each monitoring point are determined, and the environmental impact assessment results indicate the degree of environmental impact of the corresponding industrial production enterprises on the target river area during the multiple time periods.

[0014] In some embodiments, determining the environmental impact assessment result of the industrial production enterprise corresponding to each monitoring point based on the water quality change information of the water area where each monitoring point is located within the multiple time periods includes:

[0015] Determine the environmental impact assessment result of the industrial production enterprise corresponding to each monitoring point based on the water quality change information of the water area where each monitoring point is located in the multiple time periods, the water quality index of the water area where each monitoring point is located, the first weight and the second weight, wherein the water quality index is used to indicate the potability of the water area where the corresponding monitoring point is located;

[0016] The first weight is used to indicate the importance of the water quality change information to the environmental impact assessment result, and the second weight is used to indicate the importance of the water quality index to the environmental impact assessment result.

[0017] In some embodiments, the method further comprises:

[0018] Generate an industrial production optimization plan for each industrial production enterprise based on the environmental impact assessment results of the industrial production enterprise corresponding to each monitoring point;

[0019] Among them, if the environmental impact assessment result of the first industrial production enterprise corresponding to the first monitoring point indicates that the content of the target metal in the water area where the first monitoring point is located is greater than or equal to the first threshold, a first industrial production optimization plan is generated, and the first industrial production optimization plan indicates the use of a first production mode to reduce the content of the target metal in the industrial production wastewater.

[0020] In some embodiments, the method of standardizing each data in the target water quality data corresponding to each monitoring point based on multiple water quality categories to obtain a dimensionless value of each data in the target water quality data corresponding to each monitoring point includes:

[0021] Based on multiple water quality categories, each data in the target water quality data corresponding to each monitoring point is standardized by the following formula (1) and formula (2), and the dimensionless value of each data in the target water quality data corresponding to each monitoring point is obtained:

[0022]

[0023]

[0024] In the above formula, It indicates the standard value of the nth water quality category corresponding to the ith monitoring point, represents the standard value of the jth evaluation parameter corresponding to the nth water quality category, s represents the number of water quality categories, k represents the number of evaluation parameters in the target water quality data, and x ij It represents the dimensionless value of the jth evaluation parameter corresponding to the i-th monitoring point.

[0025] In some embodiments, determining a clustering reference function for each evaluation parameter in the target water quality data based on the multiple water quality categories and the dimensionless value of each data in the target water quality data corresponding to each monitoring point includes:

[0026] Based on the dimensionless value of each data in the target water quality data corresponding to the multiple water quality categories and each monitoring point, the clustering reference function of each evaluation parameter in the target water quality data is determined by the following formulas (3) to (5):

[0027]

[0028]

[0029]

[0030] In the above formula, Represents a dimensionless value x ij The cluster reference function belonging to the nth water quality category under the jth evaluation parameter, x represents the data corresponding to the jth evaluation parameter in the target water quality data.

[0031] In some embodiments, the step of determining multiple clustering coefficients for each monitoring point in each time period based on the dimensionless value of each data in the target water quality data corresponding to each monitoring point, the clustering reference function of each evaluation parameter in the target water quality data, and the clustering weight includes:

[0032] Based on the dimensionless value of each data in the target water quality data corresponding to each monitoring point, the clustering reference function of each evaluation parameter in the target water quality data, and the clustering weight, multiple clustering coefficients of each monitoring point in each time period are determined by the following formulas (6) and (7):

[0033]

[0034]

[0035] In the above formula, represents the clustering weight of the jth evaluation parameter corresponding to the nth water quality category, represents the clustering coefficient of the i-th monitoring point corresponding to the n-th water quality category, θ j Represents the preset weight of the jth evaluation parameter.

[0036] In some embodiments, determining the water quality category of the water area where each monitoring point is located in each time period based on the clustering coefficient of each monitoring point in each time period includes:

[0037] Based on a plurality of first clustering coefficients of the first monitoring point in the first time period, taking a maximum value of the plurality of first clustering coefficients as a target clustering coefficient;

[0038] The target water quality category corresponding to the target clustering coefficient is used as the water quality category to which the water area where the first monitoring point is located belongs during the first time period.

[0039] In a second aspect, the present application provides a device for evaluating the degree of impact of industrial production on river environment, the device includes at least one functional module, and the at least one functional module is used to implement the above-mentioned method for evaluating the degree of impact of industrial production on river environment.

[0040] In a third aspect, the present application provides an electronic device, comprising a processor and a memory, wherein the memory stores program code, and the processor is used to execute the program code to implement the above-mentioned method for evaluating the degree of impact of industrial production on the river environment.

[0041] In a fourth aspect, the present application provides a computer-readable storage medium, which includes: when the program code in the computer-readable storage medium is executed by a processor of an electronic device, the electronic device is enabled to execute the above-mentioned method for assessing the degree of impact of industrial production on the river environment.

[0042] In the method for evaluating the degree of impact of industrial production on the river environment provided in the embodiment of the present application, target water quality data of multiple monitoring points in the target river area in multiple time periods are obtained, and based on multiple water quality categories, fuzzy clustering is used to process each data in the target water quality data corresponding to each monitoring point to determine the water quality category to which the water area where each monitoring point is located belongs in each time period, and then according to the water quality changes in the water area where each monitoring point is located in multiple time periods, the degree of environmental impact of industrial production enterprises near each monitoring point on the target river area is evaluated. The above method improves the accuracy of the evaluation results and is convenient for providing business guidance for enterprises to optimize their production methods.

[0043] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a schematic diagram of the implementation environment of a method for assessing the impact of industrial production on the river environment;

[0045] Figure 2 It is a flow chart of a method for assessing the impact of industrial production on the river environment;

[0046] Figure 3 It is a schematic diagram of the structure of a device for evaluating the impact of industrial production on river environment;

[0047] Figure 4 It is a structural diagram of an electronic device. DETAILED DESCRIPTION

[0048] In order to enable ordinary persons in the art to better understand the technical solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0049] The data involved in this application may be data authorized by the user or fully authorized by all parties.

[0050] Figure 1 This is a schematic diagram of the implementation environment of an assessment method for the impact of industrial production on the river environment. Figure 1The implementation environment includes: a water quality monitoring device 101 and an electronic device 102. The water quality monitoring device 101 and the electronic device 102 can be directly or indirectly connected via wired or wireless communication.

[0051] The water quality monitoring device 101 is equipped with sensors that can collect concentration data of various elements in a specified water area, also known as water quality data. After collecting the water quality data, the water quality monitoring device 101 sends the collected water quality data to the electronic device 102. In some embodiments, the water quality monitoring device 101 is an intelligent Internet of Things device, such as an intelligent water test kit, which can regularly monitor water quality and regularly send the monitored water quality data to the electronic device 102.

[0052] The electronic device 102 has computing capabilities, can process the received water quality data, and output water quality change information of the designated water area and environmental impact assessment results of industrial production enterprises near the designated water area. For example, the electronic device 102 is a terminal device, such as a mobile phone, a desktop computer, a laptop, etc. For another example, the electronic device 102 is an independent physical server, or a server cluster composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, and big data and artificial intelligence platforms, but the present application is not limited thereto.

[0053] Figure 2 It is a flow chart of the method for assessing the impact of industrial production on the river environment. Figure 2 As shown, the method is executed by an electronic device and includes the following steps 201 to 207.

[0054] 201. Obtain target water quality data of multiple monitoring points in a target river basin in multiple time periods, where at least one industrial production enterprise is deployed in the land area corresponding to each monitoring point, and the target water quality data indicates the content of at least one metal in the water area where the corresponding monitoring point is located.

[0055] Among them, the target river area refers to the designated river area. This application does not limit the specific division method of the target river area. For example, the target river area is the entire river area of ​​XX province. For example, the target river area is the area where the XX identity YY river passes, and so on. There are multiple monitoring points deployed in the target river area, and each monitoring point is equipped with water quality monitoring equipment, which can collect the concentration data of various elements in the water area where the monitoring point is located, also known as water quality data. Multiple time periods refer to pre-set time periods. For example, multiple time periods refer to 20ZZ and 20WW, and this application does not limit this. At least one industrial production enterprise (which can be one or more, without limitation) is deployed in the land area corresponding to each monitoring point, wherein the industrial production enterprise includes but is not limited to chemical enterprises, mining enterprises, etc. For any monitoring point, the electronic device can obtain the target water quality data of the monitoring point in multiple time periods, and the target water quality data indicates the content of at least one metal in the water area where the monitoring point is located, wherein the metals involved in this application include but are not limited to metals included in industrial wastewater generated by industrial production, metals harmful to animals and plants, etc. For example, at least one metal includes arsenic, cadmium, iron, manganese, nickel, copper, etc., and the present application is not limited thereto. Taking at least one metal including arsenic, cadmium, and iron as an example, for any monitoring point, the target water quality data of the monitoring point includes the concentration data of arsenic, cadmium, and iron.

[0056] 202. Based on multiple water quality categories, each data in the target water quality data corresponding to each monitoring point is standardized to obtain a dimensionless value of each data in the target water quality data corresponding to each monitoring point. The water quality category is used to indicate the pollution situation of the water area.

[0057] Among them, the water quality category is pre-set, and its quantity and division method can be set according to business needs. For example, the number of water quality categories is 4, which are category 1 (good water quality, indicating that the water area is basically pollution-free), category 2 (better water quality, indicating that there is a small amount of pollution in the water area), category 3 (general water quality, indicating that there is more pollution in the water area), and category 4 (poor water quality, indicating that there is a large amount of pollution in the water area). In this step, for any monitoring point, the electronic device standardizes each data in the target water quality data of the monitoring point based on a plurality of pre-set water quality categories to obtain the dimensionless value of each data. It should be understood that the dimensionless value is a physical quantity without a unit, which can be used to compare and analyze the relative size or proportional relationship between different physical quantities. By converting the data in the target water quality data into a dimensionless value, it is convenient to unify the data corresponding to different evaluation parameters for calculation and analysis. Among them, the evaluation parameter refers to a parameter used to evaluate which water quality category a certain water quality data belongs to. For example, in this application, the evaluation parameter is at least one of the aforementioned metals. That is, the metal indicated by the evaluation parameter and the target water quality data corresponds one to one.

[0058] Exemplarily, this step includes: based on multiple water quality categories, each data in the target water quality data corresponding to each monitoring point is standardized by the following formula (1) and formula (2), so as to obtain the dimensionless value of each data in the target water quality data corresponding to each monitoring point:

[0059]

[0060]

[0061] In the above formula, It indicates the standard value of the nth water quality category corresponding to the ith monitoring point. represents the standard value of the jth evaluation parameter corresponding to the nth water quality category, s represents the number of water quality categories, k represents the number of evaluation parameters in the target water quality data, and x ij Represents the dimensionless value of the jth evaluation parameter corresponding to the ith monitoring point.

[0062] 203. Based on multiple water quality categories and the dimensionless value of each data in the target water quality data corresponding to each monitoring point, determine a clustering reference function for each evaluation parameter in the target water quality data, and the clustering reference function is used to indicate the water quality category to which the data monitored under the corresponding evaluation parameter belongs.

[0063] Among them, for any monitoring point, the electronic device calculates the clustering reference function of each evaluation parameter in the target water quality data based on multiple water quality categories and the dimensionless value of each data in the target water quality data of the monitoring point, that is, the clustering reference function corresponding to each evaluation parameter is fitted based on the target water quality data, so that it can output the water quality category to which the data belongs according to the data corresponding to each evaluation parameter.

[0064] Exemplarily, this step includes: based on the dimensionless value of each data in the target water quality data corresponding to multiple water quality categories and each monitoring point, determining the clustering reference function of each evaluation parameter in the target water quality data by the following formulas (3) to (5):

[0065]

[0066]

[0067]

[0068] In the above formula, Represents a dimensionless value x ij The cluster reference function belonging to the nth water quality category under the jth evaluation parameter, x represents the data corresponding to the jth evaluation parameter in the target water quality data.

[0069] 204. Based on the dimensionless value of each data in the target water quality data corresponding to each monitoring point, the clustering reference function of each evaluation parameter in the target water quality data, and the clustering weight, multiple clustering coefficients of each monitoring point in each time period are determined. One clustering coefficient corresponds to one water quality category, and the clustering coefficient indicates the probability that the water area where the corresponding monitoring point is located belongs to any water quality category in each time period.

[0070] For any monitoring point, the electronic device determines multiple clustering coefficients of the monitoring point in each time period based on the dimensionless value of each data in the target water quality data of the monitoring point, combined with the clustering weight and the clustering reference function of each evaluation parameter obtained in the aforementioned step 203. The clustering coefficient can indicate the probability that the water area where the monitoring point is located belongs to a certain water quality category in a certain time period.

[0071] Exemplarily, this step includes: based on the dimensionless value of each data in the target water quality data corresponding to each monitoring point, the clustering reference function of each evaluation parameter in the target water quality data, and the clustering weight, the following formulas (6) and (7) are used to determine multiple clustering coefficients of each monitoring point in each time period:

[0072]

[0073]

[0074] In the above formula, represents the clustering weight of the jth evaluation parameter corresponding to the nth water quality category, represents the clustering coefficient of the i-th monitoring point corresponding to the n-th water quality category, θ j Represents the preset weight of the jth evaluation parameter.

[0075] 205. Based on multiple clustering coefficients of each monitoring point in each time period, determine the water quality category of the water area where each monitoring point is located in each time period.

[0076] For any monitoring point, hereinafter referred to as the first monitoring point, the electronic device uses the maximum value of the multiple first clustering coefficients as the target clustering coefficient based on the multiple first clustering coefficients of the first monitoring point in the first time period; and uses the target water quality category corresponding to the target clustering coefficient as the water quality category to which the water area where the first monitoring point is located in the first time period belongs. The first time period refers to any time period among the multiple time periods.

[0077] 206. Based on the water quality category of the water area where each monitoring point is located in each time period, determine the water quality change information of the water area where each monitoring point is located in multiple time periods, and the water quality change information indicates the pollution change of the water area where the corresponding monitoring point is located in multiple time periods.

[0078] Among them, for any monitoring point, the electronic device determines the water quality change information of the water area where the monitoring point is located in multiple time periods based on the difference between the water quality categories of the water area where the monitoring point is located in each time period. For example, taking the above four water quality categories as an example, the water quality category of monitoring point A in 20ZZ is category 1, and the water quality category of monitoring point A in 20WW is category 3, indicating that the water quality of the water area where monitoring point A is located has changed from good to fair between 20ZZ and 20WW, that is, the water area where the monitoring point is located has been gradually polluted between 20ZZ and 20WW.

[0079] 207. Based on the water quality change information of the water area where each monitoring point is located in multiple time periods, the environmental impact assessment results of the industrial production enterprises corresponding to each monitoring point are determined. The environmental impact assessment results indicate the degree of environmental impact of the corresponding industrial production enterprises on the target river area in multiple time periods.

[0080] Among them, for any monitoring point, the electronic device determines the environmental impact assessment result of the industrial production enterprise corresponding to the monitoring point based on the water quality change information of the water area where the monitoring point is located. It should be understood that since industrial production enterprises are deployed near each monitoring point, and the water quality change information is obtained based on the metal content in the water area, the water quality change information can accurately reflect the impact of nearby industrial production enterprises on the river environment in multiple time periods. For example, taking the above-mentioned four water quality categories as an example, if the water quality change information indicates that it changes from category 1 to category 4, it indicates that the corresponding industrial production enterprise has a very serious environmental impact on the target river area. If the water quality change information indicates that it changes from category 1 to category 2, it indicates that the corresponding industrial production enterprise has a relatively slight environmental impact on the target river area.

[0081] In some embodiments, this step includes: based on the water quality change information of the water area where each monitoring point is located in multiple time periods, the water quality index (WQI) of the water area where each monitoring point is located, the first weight and the second weight, determine the environmental impact assessment result of the industrial production enterprise corresponding to each monitoring point, and the water quality index is used to indicate the drinkability of the water area where the corresponding monitoring point is located; wherein the first weight is used to indicate the importance of the water quality change information to the environmental impact assessment result, and the second weight is used to indicate the importance of the water quality index to the environmental impact assessment result. The first weight and the second weight are preset weights and can be set according to business needs. For example, for any monitoring point, the electronic device performs a weighted summation of the water quality change information and the water quality index based on the first weight and the second weight, and determines the environmental impact assessment result corresponding to the monitoring point according to the result of the weighted summation. By combining the water quality index, the accuracy of the environmental impact assessment result can be further improved.

[0082] In some embodiments, the electronic device can also generate an industrial production optimization plan for each industrial production enterprise based on the environmental impact assessment results of the industrial production enterprise corresponding to each monitoring point; wherein, taking the first monitoring point as an example, if the environmental impact assessment result of the first industrial production enterprise corresponding to the first monitoring point indicates that the content of the target metal in the water area where the first monitoring point is located is greater than or equal to the first threshold, a first industrial production optimization plan is generated, and the first industrial production optimization plan indicates that the first production mode is adopted to reduce the content of the target metal in the industrial production wastewater. The first threshold is a preset threshold, which can be set according to business needs. For example, if the environmental impact assessment result of industrial production enterprise A indicates that the metal cadmium in the water area where monitoring point A is located is greater than or equal to 0.05 mg / L, then a first industrial production optimization plan is generated, which indicates that the first production mode is adopted to reduce the content of metal cadmium in the industrial production wastewater. Among them, the first production mode, for example, adds a step of processing metal cadmium to the original production mode, and this application does not limit this.

[0083] In the above method, by obtaining target water quality data of multiple monitoring points in the target river area in multiple time periods, and based on multiple water quality categories, fuzzy clustering is used to process each data in the target water quality data corresponding to each monitoring point to determine the water quality category to which the water area where each monitoring point is located belongs in each time period, and then according to the water quality changes in the water area where each monitoring point is located in multiple time periods, the degree of environmental impact of industrial production enterprises near each monitoring point on the target river area is evaluated. The above method improves the accuracy of the evaluation results and is convenient for providing business guidance for enterprises to optimize production methods.

[0084] Figure 3 This is a schematic diagram of the structure of a device for evaluating the impact of industrial production on the river environment. Figure 3 The device includes an acquisition module 301, a standardization module 302, a first determination module 303, a second determination module 304, a third determination module 305, a fourth determination module 306 and a fifth determination module 307.

[0085] The acquisition module 301 is used to acquire target water quality data of multiple monitoring points in a target river area in multiple time periods, where at least one industrial production enterprise is deployed in the land area corresponding to each monitoring point, and the target water quality data indicates the content of at least one metal in the water area where the corresponding monitoring point is located;

[0086] A standardization module 302 is used to standardize each data in the target water quality data corresponding to each monitoring point based on multiple water quality categories to obtain a dimensionless value of each data in the target water quality data corresponding to each monitoring point, wherein the water quality category is used to indicate the pollution status of the water area;

[0087] A first determination module 303 is used to determine a cluster reference function of each evaluation parameter in the target water quality data based on the multiple water quality categories and the dimensionless value of each data in the target water quality data corresponding to each monitoring point, wherein the cluster reference function is used to indicate the water quality category to which the data value monitored under the corresponding evaluation parameter belongs;

[0088] The second determination module 304 is used to determine multiple clustering coefficients of each monitoring point in each time period based on the dimensionless value of each data in the target water quality data corresponding to each monitoring point, the clustering reference function of each evaluation parameter in the target water quality data, and the clustering weight, where one clustering coefficient corresponds to one water quality category, and the clustering coefficient indicates the probability that the corresponding monitoring point belongs to any water quality category in each time period;

[0089] The third determination module 305 is used to determine the water quality category of the water area where each monitoring point is located in each time period based on multiple clustering coefficients of each monitoring point in each time period;

[0090] A fourth determination module 306 is used to determine water quality change information of the water area where each monitoring point is located in the multiple time periods based on the water quality category of the water area where each monitoring point is located in each time period, wherein the water quality change information indicates the pollution change of the water area where the corresponding monitoring point is located in the multiple time periods;

[0091] The fifth determination module 307 is used to determine the environmental impact assessment results of the industrial production enterprises corresponding to each monitoring point based on the water quality change information of the water area where each monitoring point is located during the multiple time periods, and the environmental impact assessment results indicate the degree of environmental impact of the corresponding industrial production enterprise on the target river area during the multiple time periods.

[0092] In some embodiments, the fifth determination module 307 is used to determine the environmental impact assessment result of the industrial production enterprise corresponding to each monitoring point based on the water quality change information of the water area where each monitoring point is located in the multiple time periods, the water quality index of the water area where each monitoring point is located, the first weight and the second weight, wherein the water quality index is used to indicate the potability of the water area where the corresponding monitoring point is located;

[0093] The first weight is used to indicate the importance of the water quality change information to the environmental impact assessment result, and the second weight is used to indicate the importance of the water quality index to the environmental impact assessment result.

[0094] In some embodiments, the device further includes a generation module for generating an industrial production optimization plan for each industrial production enterprise based on the environmental impact assessment results of the industrial production enterprise corresponding to each monitoring point;

[0095] Among them, if the environmental impact assessment result of the first industrial production enterprise corresponding to the first monitoring point indicates that the content of the target metal in the water area where the first monitoring point is located is greater than or equal to the first threshold, a first industrial production optimization plan is generated, and the first industrial production optimization plan indicates the use of a first production mode to reduce the content of the target metal in the industrial production wastewater.

[0096] In some embodiments, the standardization module 302 is used to standardize each data in the target water quality data corresponding to each monitoring point based on multiple water quality categories by using the following formulas (1) and (2) to obtain a dimensionless value of each data in the target water quality data corresponding to each monitoring point:

[0097]

[0098]

[0099] In the above formula, It indicates the standard value of the nth water quality category corresponding to the ith monitoring point, represents the standard value of the jth evaluation parameter corresponding to the nth water quality category, s represents the number of water quality categories, k represents the number of evaluation parameters in the target water quality data, and x ij It represents the dimensionless value of the jth evaluation parameter corresponding to the i-th monitoring point.

[0100] In some embodiments, the first determination module 303 is used to determine the clustering reference function of each evaluation parameter in the target water quality data based on the dimensionless value of each data in the target water quality data corresponding to the multiple water quality categories and each monitoring point by the following formulas (3) to (5):

[0101]

[0102]

[0103]

[0104] In the above formula, Represents a dimensionless value x ij The cluster reference function belonging to the nth water quality category under the jth evaluation parameter, x represents the data corresponding to the jth evaluation parameter in the target water quality data.

[0105] In some embodiments, the second determination module 304 is used to determine multiple clustering coefficients of each monitoring point in each time period based on the dimensionless value of each data in the target water quality data corresponding to each monitoring point, the clustering reference function of each evaluation parameter in the target water quality data, and the clustering weight through the following formulas (6) and (7):

[0106]

[0107]

[0108] In the above formula, represents the clustering weight of the jth evaluation parameter corresponding to the nth water quality category, represents the clustering coefficient of the i-th monitoring point corresponding to the n-th water quality category, θ j Represents the preset weight of the jth evaluation parameter.

[0109] In some embodiments, the third determination module 305 is configured to use a maximum value of a plurality of first clustering coefficients of the first monitoring point within the first time period as a target clustering coefficient;

[0110] The target water quality category corresponding to the target clustering coefficient is used as the water quality category to which the water area where the first monitoring point is located belongs during the first time period.

[0111] In the above-mentioned device, by obtaining target water quality data of multiple monitoring points in the target river area in multiple time periods, and based on multiple water quality categories, fuzzy clustering is used to process each data in the target water quality data corresponding to each monitoring point to determine the water quality category to which the water area where each monitoring point is located belongs in each time period, and then according to the water quality changes in the water area where each monitoring point is located in multiple time periods, the degree of environmental impact of industrial production enterprises near each monitoring point on the target river area is evaluated. The above-mentioned method improves the accuracy of the evaluation results and is convenient for providing business guidance for enterprises to optimize production methods.

[0112] In some embodiments, the above device is also used to implement the above Figure 2 Other optional implementations in the method embodiment shown are not described in detail here.

[0113] Figure 4It is a structural diagram of an electronic device. The electronic device can be configured as the above-mentioned server, wherein the electronic device 400 may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) 401 and one or more memories 402, wherein the one or more memories 402 store at least one program code, and the at least one program code is loaded and executed by the one or more processors 401 to implement the process executed by the electronic device in the method for assessing the degree of impact of industrial production on the river environment provided by the above-mentioned various method embodiments. Of course, the electronic device 400 may also have components such as a wired or wireless network interface, a keyboard, and an input and output interface for input and output, and the electronic device 400 may also include other components for realizing the functions of the device, which will not be repeated here.

[0114] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0115] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for assessing the impact of industrial production on river environment, characterized in that: The method comprises: Obtain target water quality data at multiple monitoring points in a target river area in multiple time periods, where at least one industrial production enterprise is deployed in the land area corresponding to each monitoring point, and the target water quality data indicates the content of at least one metal in the water area where the corresponding monitoring point is located; Based on multiple water quality categories, each data in the target water quality data corresponding to each monitoring point is standardized to obtain a dimensionless value of each data in the target water quality data corresponding to each monitoring point, wherein the water quality category is used to indicate the pollution status of the water area; Based on the multiple water quality categories and the dimensionless value of each data in the target water quality data corresponding to each monitoring point, determine a cluster reference function for each evaluation parameter in the target water quality data, wherein the cluster reference function is used to indicate the water quality category to which the data monitored under the corresponding evaluation parameter belongs; Based on the dimensionless value of each data in the target water quality data corresponding to each monitoring point, the clustering reference function of each evaluation parameter in the target water quality data, and the clustering weight, a plurality of clustering coefficients of each monitoring point in each time period are determined, one clustering coefficient corresponds to one water quality category, and the clustering coefficient indicates the probability that the water area where the corresponding monitoring point is located belongs to any water quality category in each time period; Based on multiple clustering coefficients of each monitoring point in each time period, determine the water quality category of the water area where each monitoring point is located in each time period; Based on the water quality category of the water area where each monitoring point is located in each time period, determine the water quality change information of the water area where each monitoring point is located in the multiple time periods, and the water quality change information indicates the pollution change of the water area where the corresponding monitoring point is located in the multiple time periods; Based on the water quality change information of the water area where each monitoring point is located during the multiple time periods, the environmental impact assessment results of the industrial production enterprises corresponding to each monitoring point are determined, and the environmental impact assessment results indicate the degree of environmental impact of the corresponding industrial production enterprises on the target river area during the multiple time periods.

2. The method according to claim 1, characterized in that: Determining the environmental impact assessment results of the industrial production enterprises corresponding to each monitoring point based on the water quality change information of the water area where each monitoring point is located in the multiple time periods includes: Determine the environmental impact assessment result of the industrial production enterprise corresponding to each monitoring point based on the water quality change information of the water area where each monitoring point is located in the multiple time periods, the water quality index of the water area where each monitoring point is located, the first weight and the second weight, wherein the water quality index is used to indicate the potability of the water area where the corresponding monitoring point is located; The first weight is used to indicate the importance of the water quality change information to the environmental impact assessment result, and the second weight is used to indicate the importance of the water quality index to the environmental impact assessment result.

3. The method according to claim 1, characterized in that The method further comprises: Generate an industrial production optimization plan for each industrial production enterprise based on the environmental impact assessment results of the industrial production enterprise corresponding to each monitoring point; Among them, if the environmental impact assessment result of the first industrial production enterprise corresponding to the first monitoring point indicates that the content of the target metal in the water area where the first monitoring point is located is greater than or equal to the first threshold, a first industrial production optimization plan is generated, and the first industrial production optimization plan indicates the use of a first production mode to reduce the content of the target metal in the industrial production wastewater.

4. The method according to claim 1, characterized in that The method of standardizing each data in the target water quality data corresponding to each monitoring point based on multiple water quality categories to obtain a dimensionless value of each data in the target water quality data corresponding to each monitoring point includes: Based on multiple water quality categories, each data in the target water quality data corresponding to each monitoring point is standardized by the following formula (1) and formula (2), and the dimensionless value of each data in the target water quality data corresponding to each monitoring point is obtained: In the above formula, It indicates the standard value of the nth water quality category corresponding to the ith monitoring point, represents the standard value of the jth evaluation parameter corresponding to the nth water quality category, s represents the number of water quality categories, k represents the number of evaluation parameters in the target water quality data, and x ij It represents the dimensionless value of the jth evaluation parameter corresponding to the i-th monitoring point.

5. The method according to claim 1, characterized in that The step of determining a clustering reference function for each evaluation parameter in the target water quality data based on the multiple water quality categories and the dimensionless value of each data in the target water quality data corresponding to each monitoring point includes: Based on the dimensionless value of each data in the target water quality data corresponding to the multiple water quality categories and each monitoring point, the clustering reference function of each evaluation parameter in the target water quality data is determined by the following formulas (3) to (5): In the above formula, Represents a dimensionless value x ij The cluster reference function belonging to the nth water quality category under the jth evaluation parameter, x represents the data corresponding to the jth evaluation parameter in the target water quality data.

6. The method according to claim 1, characterized in that The method of determining multiple clustering coefficients of each monitoring point in each time period based on the dimensionless value of each data in the target water quality data corresponding to each monitoring point, the clustering reference function of each evaluation parameter in the target water quality data, and the clustering weight includes: Based on the dimensionless value of each data in the target water quality data corresponding to each monitoring point, the clustering reference function of each evaluation parameter in the target water quality data, and the clustering weight, multiple clustering coefficients of each monitoring point in each time period are determined by the following formulas (6) and (7): In the above formula, represents the clustering weight of the jth evaluation parameter corresponding to the nth water quality category, represents the clustering coefficient of the i-th monitoring point corresponding to the n-th water quality category, θ j Represents the preset weight of the jth evaluation parameter.

7. The method according to claim 1, characterized in that The method of determining the water quality category of the water area where each monitoring point is located in each time period based on the clustering coefficient of each monitoring point in each time period includes: Based on a plurality of first clustering coefficients of the first monitoring point in the first time period, taking a maximum value of the plurality of first clustering coefficients as a target clustering coefficient; The target water quality category corresponding to the target clustering coefficient is used as the water quality category to which the water area where the first monitoring point is located belongs during the first time period.

8. An evaluation device for the impact of industrial production on river environment, characterized in that: The device comprises: An acquisition module is used to acquire target water quality data of multiple monitoring points in a target river area in multiple time periods, where at least one industrial production enterprise is deployed in the land area corresponding to each monitoring point, and the target water quality data indicates the content of at least one metal in the water area where the corresponding monitoring point is located; A standardization module, for standardizing each data in the target water quality data corresponding to each monitoring point based on multiple water quality categories, to obtain a dimensionless value of each data in the target water quality data corresponding to each monitoring point, wherein the water quality category is used to indicate the pollution status of the water area; A first determination module is used to determine a cluster reference function of each evaluation parameter in the target water quality data based on the multiple water quality categories and the dimensionless value of each data in the target water quality data corresponding to each monitoring point, wherein the cluster reference function is used to indicate the water quality category to which the data value monitored under the corresponding evaluation parameter belongs; A second determination module is used to determine multiple clustering coefficients of each monitoring point in each time period based on the dimensionless value of each data in the target water quality data corresponding to each monitoring point, the clustering reference function of each evaluation parameter in the target water quality data, and the clustering weight, wherein one clustering coefficient corresponds to one water quality category, and the clustering coefficient indicates the probability that the corresponding monitoring point belongs to any water quality category in each time period; A third determination module is used to determine the water quality category of the water area where each monitoring point is located in each time period based on multiple clustering coefficients of each monitoring point in each time period; A fourth determination module is used to determine the water quality change information of the water area where each monitoring point is located in the multiple time periods based on the water quality category of the water area where each monitoring point is located in each time period, wherein the water quality change information indicates the pollution change of the water area where the corresponding monitoring point is located in the multiple time periods; The fifth determination module is used to determine the environmental impact assessment results of the industrial production enterprises corresponding to each monitoring point based on the water quality change information of the water area where each monitoring point is located within the multiple time periods, and the environmental impact assessment results indicate the degree of environmental impact of the corresponding industrial production enterprise on the target river area within the multiple time periods.

9. An electronic device, characterized in that: The electronic device includes a processor and a memory, the memory stores program code, and the processor is used to execute the program code to implement the method for evaluating the impact of industrial production on the river environment as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: When the program code in the computer-readable storage medium is executed by a processor of an electronic device, the electronic device is enabled to execute the method for evaluating the impact of industrial production on the river environment as described in any one of claims 1 to 7.

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