Method for analyzing systematic governance effect of urban water environment, and device

Abstract

The present application relates to the technical field of water environment governance. Provided are a method for analyzing the systematic governance effect of an urban water environment, and a device. The method comprises: reading a set of first dimensions from a storage device; on the basis of an inspection probability of each first dimension and a degree of correlation between analysis results of every two first dimensions, screening out second dimensions from the set of first dimensions, so as to form a set of second dimensions; determining a comprehensive effectiveness degree of the set of second dimensions, and determining a stability degree of the set of second dimensions; when the comprehensive effectiveness degree is greater than or equal to a preset effectiveness threshold value and the stability degree is greater than or equal to a preset stability threshold value, analyzing the systematic governance effect of an urban water environment on the basis of the set of second dimensions, so as to obtain an analysis result of the governance effect; and displaying the analysis result of the systematic governance effect of the urban water environment. The method in the present application solves the problem of how to objectively, scientifically and accurately analyze the systematic governance effect of an urban water environment.

Description

System governance effect analysis method and device for urban water environment

[0001] The present application claims priority to the Chinese patent application No. 202411354804.1, filed on September 27, 2024, and entitled "System governance effect analysis method and device for urban water environment", the whole content of which is incorporated herein by reference. TECHNICAL FIELD

[0002] The present application relates to the technical field of water environment governance, in particular to a system governance effect analysis method and device for urban water environment. BACKGROUND

[0003] Urban water environment governance involves multiple factors such as pollution sources, drainage networks, sewage treatment plants, rivers and lakes, and shorelines. Currently, there are analysis methods for the governance effect of sewage treatment plants, drainage facilities, rivers and lakes, etc., but there is a lack of a set of analysis methods covering water resources, water environment and water ecological governance effect. At the same time, the current factor analysis system has the problems of strong subjectivity, weak logical correlation and large system cognition deviation, which makes it difficult to objectively, scientifically and accurately reflect the level and short board of urban water environment system governance.

[0004] Therefore, how to objectively, scientifically and accurately analyze the system governance effect of urban water environment is a problem to be solved by the present application. SUMMARY

[0005] The present application provides a system governance effect analysis method and device for urban water environment to solve the problem of how to objectively, scientifically and accurately analyze the system governance effect of urban water environment.

[0006] In a first aspect, the present application provides a system governance effect analysis method for urban water environment, which comprises:

[0007] reading a first dimension set from a storage device, wherein the first dimension set comprises a plurality of first dimensions for analyzing the system governance effect of urban water environment;

[0008] determining the test probability of each first dimension according to the analysis result of each first dimension for multiple cities, and determining the correlation degree between the analysis results of each two first dimensions, and screening the second dimensions from the first dimension set according to the test probability of each first dimension and the correlation degree between the analysis results of each two first dimensions to form a second dimension set;

[0009] determining the comprehensive effective degree of the second dimension set according to the difference between the preset analysis effect values of each second dimension, and determining the stability degree of the second dimension set according to the similarity degree between the analysis effect value of each second dimension and the target effect value;

[0010] When the comprehensive effective degree is greater than or equal to the preset effective threshold and the stability degree is greater than or equal to the preset stability threshold, the system governance effect of the urban water environment is analyzed according to the second dimension set, and a governance effect analysis result is obtained.

[0011] The system governance effect analysis result of the urban water environment is displayed.

[0012] Optionally, the test probability of each first dimension is determined according to the analysis result of the plurality of cities for each first dimension, including:

[0013] For each first dimension, the analysis result of the plurality of cities for the first dimension is determined.

[0014] For each first dimension, the test probability of the first dimension is determined according to the corresponding analysis result of the plurality of cities for the first dimension, and the test probability of the first dimension is positively correlated with the corresponding analysis result of the plurality of cities for the first dimension.

[0015] Optionally, the correlation degree between the analysis results of each two first dimensions is determined, including:

[0016] For each first dimension, the average analysis result of each first dimension is determined by taking the average value of the corresponding analysis result of the plurality of cities for the first dimension.

[0017] For any two first dimensions, the corresponding analysis result of the plurality of cities for the two first dimensions and the average analysis result of the two first dimensions are input into a Pearson correlation model to obtain the correlation degree between the analysis results of the two first dimensions.

[0018] Optionally, the second dimensions are selected from the first dimension set according to the test probability of each first dimension and the correlation degree between the analysis results of each two first dimensions to form the second dimension set, including:

[0019] The first dimensions with a test probability less than a preset test probability are selected from the first dimension set to obtain a second dimension set composed of at least one second dimension.

[0020] One of each two second dimensions in the second dimension set with a correlation degree greater than or equal to a preset correlation degree is deleted.

[0021] Optionally, the comprehensive effective degree of the second dimension set is determined according to the difference between the preset analysis effect values of each second dimension, including:

[0022] For each second dimension, the average analysis effect value of the second dimension is determined according to the plurality of analysis effect values corresponding to the second dimension.

[0023] For each second dimension, determining an effective degree of the second dimension according to the plurality of analysis effect values corresponding to the second dimension and the average analysis effect value of the second dimension;

[0024] According to the effective degree of each second dimension in the second dimension set, determining a comprehensive effective degree of the second dimension set.

[0025] Optionally, according to the similarity between the analysis effect value of each second dimension and the target effect value, determining a stability degree of the second dimension set, comprising:

[0026] For each second dimension, taking the average analysis effect value of the second dimension as the target effect value;

[0027] According to the similarity between the analysis effect value corresponding to each second dimension and the target effect value of each second dimension, determining a stability degree of the second dimension set.

[0028] Optionally, after determining the comprehensive effective degree of the second dimension set according to the difference between the preset analysis effect values of each second dimension, and determining the stability degree of the second dimension set according to the similarity between the analysis effect value of each second dimension and the target effect value, the method further comprises:

[0029] When the comprehensive effective degree is less than a preset effective threshold and / or the stability degree is less than a preset stability threshold, returning to the step of reading the first dimension set from the storage device.

[0030] Optionally, when the comprehensive effective degree is greater than or equal to the preset effective threshold and the stability degree is greater than or equal to the preset stability threshold, before analyzing the system management effect of the urban water environment according to the second dimension set to obtain the management effect analysis result, the method further comprises:

[0031] Obtaining a plurality of difficulty factors corresponding to each second dimension of the second dimension set, the difficulty factor being used to indicate the analysis difficulty of the second dimension;

[0032] For each second dimension, after deleting the maximum value and the minimum value in the plurality of difficulty factors corresponding to the second dimension, determining an average difficulty factor of the second dimension set according to the average value of the plurality of difficulty factors of each second dimension;

[0033] When the average difficulty factor of the second dimension set is greater than a preset difficulty factor threshold, adjusting the analysis strategy of each second dimension of the second dimension set.

[0034] In a second aspect, the present application provides a system management effect analysis device for urban water environment, comprising:

[0035] The reading module is configured to read a first dimension set from the storage device, wherein the first dimension set comprises a plurality of first dimensions for analyzing the system management effect of the urban water environment;

[0036] The screening module is configured to determine a test probability of each first dimension according to the analysis result of the plurality of cities for each first dimension, determine a correlation degree between the analysis results of each two first dimensions, and screen a second dimension from the first dimension set according to the test probability of each first dimension and the correlation degree between the analysis results of each two first dimensions to form a second dimension set.

[0037] The determining module is configured to determine a comprehensive effective degree of the second dimension set according to a difference between the preset analysis effect values of each second dimension, and determine a stability degree of the second dimension set according to a similarity degree between the analysis effect value and the target effect value of each second dimension.

[0038] The analysis module is configured to analyze the system management effect of the urban water environment according to the second dimension set when the comprehensive effective degree is greater than or equal to a preset effective threshold and the stability degree is greater than or equal to a preset stability threshold, and obtain a management effect analysis result.

[0039] The display module is configured to display the system management effect analysis result of the urban water environment.

[0040] In a third aspect, the present application provides an electronic device, comprising a processor and a memory connected with the processor in communication;

[0041] The memory stores computer execution instructions;

[0042] When the processor executes the computer execution instructions stored in the memory, the processor is configured to implement the urban water environment system management effect analysis method of the first aspect.

[0043] In a fourth aspect, the present application provides a computer readable storage medium, wherein the computer readable storage medium stores computer execution instructions, and when the computer execution instructions are executed by a processor, the computer execution instructions are configured to implement the urban water environment system management effect analysis method of the first aspect.

[0044] In a fifth aspect, the present application provides a computer program product, comprising a computer program, and when the computer program is executed by a processor, the computer program is configured to implement the urban water environment system management effect analysis method of the first aspect.

[0045] The application provides a system management effect analysis method and device for urban water environment, which comprises the following steps: reading a first dimension set from a storage device, wherein the first dimension set comprises a plurality of first dimensions for analyzing the system management effect of the urban water environment; determining the test probability of each first dimension according to the analysis result of each first dimension for a plurality of cities, and determining the correlation degree between the analysis results of each two first dimensions, and screening a second dimension from the first dimension set according to the test probability of each first dimension and the correlation degree between the analysis results of each two first dimensions to form a second dimension set; determining the comprehensive effective degree of the second dimension set according to the difference between the preset analysis effect values of each second dimension, and determining the stability degree of the second dimension set according to the similarity between the analysis effect value and the target effect value of each second dimension; when the comprehensive effective degree is greater than or equal to a preset effective threshold and the stability degree is greater than or equal to a preset stability threshold, analyzing the system management effect of the urban water environment according to the second dimension set to obtain a management effect analysis result; and displaying the system management effect analysis result of the urban water environment. The test probability and the correlation degree are used to screen a plurality of dimensions for analyzing the system management effect of the urban water environment, and the system management effect analysis method for the urban water environment is constructed, so that the problem of how to objectively, scientifically and accurately analyze the system management effect of the urban water environment is solved; the comprehensive effective degree and the stability degree of the second dimension set are determined to ensure the effectiveness and stability of the system management effect analysis of the urban water environment. BRIEF DESCRIPTION OF DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without any creative effort.

[0047] Fig. 1 is a flow diagram of a system management effect analysis method for urban water environment according to an embodiment of the present application;

[0048] Fig. 2 is a flow diagram of a system management effect analysis method for urban water environment according to an embodiment of the present application;

[0049] Fig. 3 is a structural diagram of a system management effect analysis device for urban water environment according to an embodiment of the present application;

[0050] Fig. 4 is a structural diagram of the hardware of an electronic device according to an embodiment of the present application.

[0051] 400 - system management effect analysis device of urban water environment; 410 - reading module; 420 - screening module; 430 - determination module; 440 - analysis module; 450 - display module; 500 - electronic device; 510 - processor; 520 - memory; 530 - communication component; 540 - bus. DETAILED DESCRIPTION

[0052] The exemplary embodiments will be described in detail herein with reference to the accompanying drawings. In the following description, unless otherwise indicated, like numbers in the different drawings represent the same or similar elements. The following exemplary embodiments described in the detailed description are not meant to be an all-inclusive description of all aspects of the application. Rather, they are merely examples of apparatus and methods in accordance with aspects of the application as detailed in the appended claims.

[0053] In the embodiments of the present application, the same or similar items or similar items with substantially the same functions and effects are distinguished by using "first", "second", etc. Those skilled in the art can understand that "first", "second", etc. do not limit the quantity and execution order, and "first", "second", etc. do not necessarily mean different. It should be noted that in the embodiments of the present application, "exemplary" or "for example" is used to represent an example, illustration or description. Any embodiment or design scheme described as "exemplary" or "for example" in the present application should not be interpreted as more optional or more advantageous than other embodiments or design schemes. Rather, the use of "exemplary" or "for example" is intended to present the relevant concept in a specific manner. In the embodiments of the present application, "at least one" means one or more, and "multiple" means two or more.

[0054] It should be noted that "at the time of" in the embodiments of the present application can be at the moment when a certain condition occurs, or within a period of time after a certain condition occurs, which is not specifically limited in the embodiments of the present application. In addition, the urban water environment system management effect analysis method provided in the embodiments of the present application is only an example, and the urban water environment system management effect analysis method can also include more or less content.

[0055] There are analysis methods for the management effect of sewage treatment plants, drainage facilities, rivers and lakes and other elements in the prior art, but there is a lack of an analysis method covering water resources, water environment and water ecological management effect. At the same time, the current element analysis system has the problems of strong subjectivity, weak logical correlation and large system cognition deviation, and it is difficult to objectively, scientifically and accurately reflect the level and short board of urban water environment system management.

[0056] The embodiment of the present application provides a system management effect analysis method and device for urban water environment, which can be used in the technical field of water environment management, and aims to solve the above technical problems of the prior art.

[0057] Fig. 1 is a flow diagram of a system management effect analysis method for urban water environment according to an embodiment of the present application. As shown in Fig. 1, the method comprises the following steps:

[0058] S101, reading a first dimension set from a storage device.

[0059] Specifically, the first dimension set comprises a plurality of first dimensions for analyzing the system management effect of urban water environment, and each dimension is an index for analyzing the system management effect of urban water environment, for example, urban flood control project compliance rate, urban drainage compliance area, etc. The storage device is a device for storing information, such as a mobile hard disk or a database, etc.

[0060] The reference method and network structure analysis method are used to select a plurality of first dimensions related to "water resources", "water environment" and "water ecology" from the literature database, to constitute a first dimension set and to be stored, and to read the first dimension set from the storage device.

[0061] S102, determining the test probability of each first dimension according to the analysis result of each first dimension for a plurality of cities, and determining the correlation degree between the analysis results of each two first dimensions, and selecting a second dimension from the first dimension set according to the test probability of each first dimension and the correlation degree between the analysis results of each two first dimensions, to constitute a second dimension set.

[0062] Specifically, the analysis result of each first dimension for a city can be represented by a numerical value, and each first dimension corresponds to a formula, so that the analysis result of the first dimension for a city can be calculated by the formula. For example, the urban flood control project compliance rate can be calculated by urban drainage compliance area ÷ total area of the region with clear drainage tasks and targets × 100%.

[0063] The test probability is used to indicate the significance level of the corresponding dimension, that is, the influence degree of the first dimension on the system governance effect of the urban water environment, and the correlation degree is used to indicate the correlation between the two dimensions. According to each first dimension in the first dimension set, a plurality of cities are analyzed to obtain a plurality of analysis results of different dimensions of each city, wherein the plurality of cities can be ten cities or other values. The analysis results are input, and the test probability of each dimension is determined by hypothesis testing method, and the hypothesis testing can be Z test, chi-square test, Wald test, etc. The correlation degree can be represented by a correlation coefficient, such as Pearson correlation coefficient and Spearman correlation coefficient. The analysis results are input, and the correlation degree is obtained by correlation analysis. The correlation degree is related to the similarity of the analysis results of each two first dimensions on the plurality of cities.

[0064] The second dimension includes: the first dimension with a test probability greater than or equal to a preset test probability, two of each two first dimensions with a correlation degree less than a preset correlation degree, and one of each two first dimensions with a higher test probability with a correlation degree greater than or equal to a preset correlation degree.

[0065] S103, according to the difference between the analysis effect values of each second dimension, determine the comprehensive effective degree of the second dimension set, and according to the similarity between the analysis effect value and the target effect value of each second dimension, determine the stability degree of the second dimension set.

[0066] Specifically, the analysis effect value is a numerical value indicating the analysis effect of using the second dimension for analysis, which is set by an expert in advance. The effective degree is used to measure the deviation degree of the expert's cognition of the second dimension. The greater the deviation degree, the less the effective degree, the more the effective degree, and the more the effective degree. The target effect value is the ideal value of the analysis effect value. The stability degree is used to indicate the stability of the analysis result obtained by analyzing the system governance effect of the urban water environment according to the second dimension set. According to the difference between the analysis effect values of each second dimension, the effective degree of each second dimension is determined, and then the comprehensive effective degree of the second dimension set is determined. The greater the difference between the analysis effect values of the second dimension, the less the comprehensive effective degree, and the more the comprehensive effective degree. The similarity between the analysis effect value and the corresponding target effect value of each second dimension is determined to determine the stability degree of the second dimension set. The greater the similarity, the closer to the target effect value, and the better the stability of the second dimension set, and then the stability degree of the second dimension set is determined.

[0067] S104, when the comprehensive effective degree is greater than or equal to the preset effective threshold value and the stability degree is greater than or equal to the preset stability threshold value, analyzing the system management effect of the urban water environment according to the second dimension set to obtain a management effect analysis result.

[0068] Specifically, the preset effective threshold value and the preset stability threshold value can be valued according to actual conditions. The preset effective threshold value is to ensure that each dimension has a certain significance, while avoiding too strict conditions leading to a lack of representativeness of the remaining dimensions. The preset stability threshold value is to ensure that dimensions with relatively large correlation can be deleted, while avoiding too broad conditions leading to redundancy in the analysis system. When the comprehensive effective degree and the stability degree meet the conditions, the urban water environment management effect is quantitatively calculated according to the evaluation content and method of each dimension in the second dimension set to obtain the management effect analysis result. The management effect analysis result can include the analysis result of each second dimension on the urban water environment, and / or the comprehensive calculation result of the analysis result of all second dimensions on the urban water environment. The comprehensive calculation result can be a calculated value after processing the analysis result of all second dimensions, for example, an average value, a weighted cumulative value.

[0069] S105, displaying the system management effect analysis result of the urban water environment.

[0070] Specifically, the analysis of the urban water environment management effect can be displayed in the form of a chart at each dimension, and can also be compared with the analysis result of the water environment management level leading city to directly display the comprehensive analysis result according to the difference. For example, if the analysis result difference is less than 10%, the management effect is considered good; if the analysis result difference is 10%-20%, the management effect is considered better; if the analysis result difference is 20%-30%, the management is considered to be poor; and if the analysis result difference is greater than 30%, the management effect is considered to be poor.

[0071] The application provides a system management effect analysis method of urban water environment, including: reading a first dimension set from a storage device, wherein the first dimension set includes a plurality of first dimensions for analyzing the system management effect of the urban water environment; determining the test probability of each first dimension according to the analysis result of a plurality of cities of each first dimension, and determining the correlation degree between the analysis results of each two first dimensions, and screening a second dimension from the first dimension set according to the test probability of each first dimension and the correlation degree between the analysis results of each two first dimensions, to form a second dimension set; determining the comprehensive effective degree of the second dimension set according to the difference between the preset analysis effect values of each second dimension, and determining the stability degree of the second dimension set according to the similarity between the analysis effect value and the target effect value of each second dimension; when the comprehensive effective degree is greater than or equal to a preset effective threshold and the stability degree is greater than or equal to a preset stability threshold, analyzing the system management effect of the urban water environment according to the second dimension set to obtain a management effect analysis result; and displaying the system management effect analysis result of the urban water environment. The application filters a plurality of dimensions for analyzing the system management effect of the urban water environment by using the test probability and the correlation degree, constructs the system management effect analysis method of the urban water environment, solves the problem of how to objectively, scientifically and accurately analyze the system management effect of the urban water environment, and determines the comprehensive effective degree and the stability degree of the second dimension set to ensure the effectiveness and stability of the system management effect analysis of the urban water environment.

[0072] Fig. 2 is a flowchart of a system management effect analysis method of urban water environment provided by an embodiment of the application. The embodiment describes the system management effect analysis method of the urban water environment in detail based on the embodiment of Fig. 1. As shown in Fig. 2, the method includes:

[0073] S201, reading a first dimension set from a storage device.

[0074] S201 is similar to S101, and the embodiment will not be described herein.

[0075] S202, for each first dimension, determine the analysis result of the first dimension on the plurality of cities; for each first dimension, determine the test probability of the first dimension according to the analysis result corresponding to the first dimension on the plurality of cities; for each first dimension, take the average value of the analysis result corresponding to the first dimension on the plurality of cities as the average analysis result of each first dimension; for any two first dimensions, input the analysis result corresponding to the two first dimensions on the plurality of cities and the average analysis result of the two first dimensions into a Pearson correlation model to obtain the correlation degree between the analysis results of the two first dimensions; and filter out the first dimensions with test probabilities less than a preset test probability from the first dimension set to obtain a second dimension set composed of at least one second dimension; and delete one of each two second dimensions with a correlation degree greater than or equal to a preset correlation degree in the second dimension set.

[0076] Specifically, the Wald test can be used for the first screening to screen out the dimensions that can significantly distinguish the water environment treatment effect of the cities. First, it is assumed that β i = 0, that is, the i-th first dimension has no significant influence on the analysis of the system treatment effect of the water environment of the city. The Wald value of the i-th first dimension is calculated by using formula (1), and the specific formula is as follows:

[0077] In the formula: Wi is the Wald value of the i-th first dimension, β i is the Logistic regression coefficient estimate value of the i-th first dimension, S i is the Logistic regression coefficient standard deviation of the i-th first dimension, wherein the Logistic regression model is shown in formula (2):

[0078] In the formula: p i is the test probability of the i-th first dimension, β0 is a constant, the independent variable X ik is the analysis result of the i-th first dimension on the water environment treatment effect of the k-th city, and n represents the number of cities, which can be taken as 10 here.

[0079] Before calculating the Wald value, a plurality of cities with known analysis results of the above dimensions are selected, and then the analysis result data is imported into an analysis software such as the SPSS software. Through the binary Logistic regression program, the regression coefficient, standard deviation (S i ), Wald value and test probability (p i ) corresponding to the Wald value of each dimension are obtained. The test probability p iThe preset test probability can be p0, which can be preset as 0.10. The dimensions with test probabilities lower than p0 are reserved to obtain a second dimension set. The preset test probability is valued according to actual conditions. The setting of 0.10 can make the reserved dimensions have a certain significance, and avoid too strict conditions leading to lack of representativeness of the remaining dimensions.

[0080] The correlation degree is obtained by using correlation analysis, and the second screening of the dimensions is performed to screen out the dimensions that have greater influence on the water environment treatment effect analysis and reflect different information, so as to avoid overlapping of analysis results between the dimensions. The Pearson correlation model can be selected for the correlation analysis. The calculation formula (3) of the correlation degree is as follows:

[0081] In the formula, r ij represents the correlation degree between the i th first dimension and the j th first dimension, x ik represents the analysis result of the i th first dimension of the k th city, x jk represents the analysis result of the j th first dimension of the k th city, represents the average analysis result of the i th first dimension, represents the average analysis result of the j th first dimension, and n represents the number of cities, which can be 10.

[0082] The correlation degree r ij between the i th first dimension and the j th first dimension is compared with a preset correlation degree r0. ij If r ij < r0, it is considered that the i th first dimension and the j th first dimension are not correlated, and then the i th dimension and the j th dimension are reserved.

[0083] S203, for each second dimension, an average analysis effect value of the second dimension is determined according to a plurality of analysis effect values corresponding to the second dimension; for each second dimension, an effective degree of the second dimension is determined according to the plurality of analysis effect values corresponding to the second dimension and the average analysis effect value of the second dimension; a comprehensive effective degree of the second dimension set is determined according to the effective degrees of the second dimensions in the second dimension set; for each second dimension, the average analysis effect value of the second dimension is taken as a target effect value; and a stability degree of the second dimension set is determined according to a similarity degree between the analysis effect values corresponding to each second dimension and the target effect value of each second dimension.

[0084] Assuming the number of experts is J, the analysis effect value set by each expert for the second dimension set F = {f1, f2, f3…f n} is obtained, and the analysis effect value set by the jth expert for the ith second dimension is denoted as x ij The comprehensive effective degree is denoted as γ, and the specific calculation formula is as follows:

[0085] In the formula: is the average analysis effect value of the ith second dimension f i , x ij is the analysis effect value set by the jth expert for the ith second dimension, M is the maximum value of the multiple analysis effect values of the ith second dimension, γ i is the effective degree of the ith second dimension, n is the number of second dimensions in the second dimension set, and γ is the comprehensive effective degree of the second dimension set.

[0086] The smaller the effective degree, the more consistent the understanding of each expert for the problem when using the dimension analysis, and the higher the rationality of the analysis system; otherwise, the lower the effective degree.

[0087] Assuming that there is a set of analysis data that can completely and truly reflect the essence of the analysis object, then the set of data is the ideal value, and the closer the analysis data obtained by using the analysis system to the set of data, the more the analysis system can reflect the true situation of the analysis object, and the higher the stability of the analysis system. Therefore, the correlation coefficient can be used as the stability degree of the analysis system to reflect the stability of the analysis system.

[0088] The target effect value is the ideal value of the analysis effect value, and the mean value of the J analysis effect values of each second dimension can be used as the target effect value. The correlation coefficient between the Jth analysis effect value and the target effect value is used as the stability degree and is denoted as ρ j . The larger the ρ j , the greater the correlation between the analysis result and the ideal value, and the closer to the ideal value, and the better the stability of the analysis system; otherwise, the stability of the analysis system is poor and needs to be corrected.

[0089] The average analysis effect value set of the multiple experts for the second dimension set F = {f1, f2, f3…f n} is Y = {y1, y2, y3…y n}, and Y = {y1, y2, y3…y n} is used as the target effect value set of each second dimension, wherein y i is equal to x The analysis effect value set X j = {x 1j , x2j , x 3j …x nj} and the target effect value set Y = {y1, y2, y3…y n} and the stability degree p j are calculated by formula (7) and (8), specifically as follows:

[0090] In the formula: |p j |≤1, p j is the stability degree, n is the number of the second dimensions in the second dimension set, x ij is the analysis effect value set by the jth expert for the ith second dimension, y is the average analysis effect value of the ith second dimension, y i is the average analysis effect value of the ith second dimension, and y is the average analysis effect value of each second dimension in the second dimension set.

[0091] S204, when the comprehensive effective degree is less than the preset effective threshold and / or the stability degree is less than the preset stability threshold, returning to the step of reading the first dimension set from the storage device.

[0092] Specifically, the preset effective threshold and the preset stability threshold can be actual values, for example, 0.2 and 0.9, which are used in the following description. When the dimension set F has γ≥0.2 and p j ≥0.9, it is considered that the analysis result is effective and stable, and optimization is not needed; when γ<0.2 and / or p<0.9, it is indicated that the dimension set lacks effectiveness or stability, and the multiple first dimensions are re-screened to form the first dimension set and stored, and the first dimension set is read from the storage device and re-screened until the conditions are met.

[0093] In an example, the finally obtained second dimension set includes multiple dimensions in three aspects of water resources, water environment and water ecology. Specifically, the water resources include: urban flood control engineering compliance rate, urban drainage area, rainwater annual runoff pollution load reduction rate, key river and lake ecological flow compliance rate, water system connectivity; the water environment includes: drainage network health degree, urban domestic sewage centralized collection rate, annual overflow volume control rate, sewage treatment rate, sewage plant pollution load additional reduction rate, river and lake water function area water quality compliance rate, water body eutrophication index; the water ecology includes: ecological shoreline rate, river curvature, benthic macroinvertebrate diversity index.

[0094] Secondly, the evaluation content and method of each dimension in the second dimension set are determined, following the principles of easy monitoring and easy calculation to improve the practicability of the analysis system.

[0095] In terms of water resources, for the standard rate of urban flood control projects, urban flood control projects mainly involve facilities such as flood interception ditches, dams, and flood control (tide) gates. The design standards, operating conditions, and operation and maintenance efficiency of the above-mentioned facilities are common evaluation contents. In some studies, the standard of flood control facilities is used as a comprehensive evaluation index of flood control effect. However, the flood control standards of different cities and different regions are different. Therefore, the evaluation is carried out by comparing and analyzing the actual construction standard and the design standard of urban flood control projects, and the calculation formula is: the number of urban flood control projects that meet the design standard ÷ the total number of urban flood control projects × 100%.

[0096] In terms of urban drainage standard area, urban drainage projects mainly involve facilities such as drainage pipe networks and strong drainage pumping stations. Their design standards, operating conditions, and operation and maintenance efficiency are common evaluation contents. In some studies, the elimination rate of waterlogging points is used as a comprehensive evaluation index of waterlogging prevention effect. However, the selection of waterlogging points consumes a lot of manpower and material resources, and the calculation and evaluation are difficult, and the severity of waterlogging is not fully reflected. Therefore, the proportion of urban drainage standard area to the area with drainage tasks is selected as the evaluation content, and the calculation formula is: urban drainage standard area ÷ total area of regions with clear drainage tasks and targets × 100%.

[0097] In terms of rainwater runoff pollution load reduction rate, runoff pollution can be purified by natural or artificial facilities with the functions of "seepage, detention, storage, purification, use, and drainage". Therefore, the reduction level of runoff pollution load of the above-mentioned facilities is calculated to reflect the runoff pollution load reduction rate, and the calculation formula is: the reduced suspended pollution load in the annual average rainfall ÷ the average total amount of runoff suspended pollution load in the rainfall ÷ 100%, wherein the reduced suspended pollution load in the rainfall = runoff seepage volume of the facility × runoff pollution suspended pollution reduction concentration; runoff seepage volume of the facility = saturated permeability coefficient of the facility × hydraulic slope × effective permeation area × runoff infiltration duration; runoff pollution suspended pollution reduction concentration = average concentration of rainfall runoff pollution suspended pollution - average concentration of suspended pollution of effluent water; total amount of runoff suspended pollution load in rainfall = rainfall × receiving area × average concentration of rainfall runoff pollution suspended pollution.

[0098] In terms of the standard rate of key river and lake ecological flow, good base flow is the basis for protecting water environment self-purification capacity and good ecology. For this reason, functional rivers and lakes generally have ecological flow control targets. Therefore, the proportion of time that meets the river and lake ecological flow control target is used to reflect the river and lake ecological flow standard rate, and the calculation formula is: the number of days that meets the river and lake ecological flow control target ÷ the number of days in a year × 100%.

[0099] For water system connectivity, water system connectivity is also an important factor to protect the self-purification capacity of water environment. In some studies, the number of artificial buildings per 100 km of river length that block the connectivity of rivers is used to represent the connectivity of urban rivers. However, this method cannot fully reflect the natural connection of river channels, river headstreams, etc. Therefore, the ratio of the number of river chains to the maximum possible number of river chains is used to reflect the connectivity of river and lake systems. The river intersection is a node, and the river between two adjacent nodes is called a river chain. The calculation formula is: the number of river chains ÷ [3 × (the number of nodes - 2)].

[0100] In terms of water environment, for the health of the drainage network, for the efficiency analysis of the drainage collection system, the drainage network coverage rate, the total length of the pipe network, etc. can evaluate its service capacity, and the functional defects and structural defects of the pipe network are used to evaluate the quality of the conveying facilities. Therefore, by calculating the number, length, and position of various defects of the pipe network, the health index of the pipe network is reflected. The calculation formula is: X I = (R I + M I ) ÷ 2, where R I represents the pipe segment repair index calculated according to the pipe segment structural defect score, R I = 0.7 × F + 0.1 × K + 0.05 × E + 0.05 × T + 0.05 × J + 0.05 × M, F represents the pipe segment structural defect parameter, which is determined according to the pipe segment damage condition parameter S, S is calculated according to the number of defects, longitudinal clearance, and defect type, K represents the regional importance parameter (central business, traffic trunk, and other driving roads, etc.), E represents the pipe importance parameter (determined according to the pipe diameter); T represents the soil influence parameter (loess, expansive soil, clay, etc.); J represents the pipe structure influence parameter (flexible, rigid); M I represents the pipe interface form influence parameter (flexible, rigid); M I = 0.8 × G + 0.15 × K + 0.05 × E, G represents the pipe segment functional defect parameter, which is determined according to the pipe segment operation condition parameter Y, Y is calculated according to the number of functional defects, longitudinal clearance, and defect type; K represents the regional importance parameter (central business, traffic trunk, and other driving roads, etc.), E represents the pipe importance parameter (determined according to the pipe diameter).

[0101] For the centralized collection rate of urban domestic sewage, this indicator can reflect the service effect of the urban domestic sewage collection system, thereby comprehensively analyzing the collection range and efficiency of the pipe network. Currently, the chemical oxygen demand (COD) collection concentration is often used to calculate the sewage collection rate. However, the COD concentration is easily disturbed by industrial wastewater. Therefore, the biochemical oxygen demand (BOD) collection concentration is used to calculate the collection rate. The calculation formula is: (the amount of sewage entering the sewage treatment plant × the BOD concentration of sewage treatment) ÷ (the daily BOD discharge per capita × the total population of the urban area) × 100%.

[0102] For the annual overflow volume control rate, in the stage of turning point source pollution control to non-point source pollution control, in addition to rainfall runoff, combined sewer overflow pollution is also an important source of non-point source pollution. Although there are evaluation indexes for overflow pollution load control, the load is affected by many factors such as rainfall duration, rainfall intensity, and rainwater concentration, making it difficult to monitor and calculate. Therefore, the overflow pollution volume reduction is used to reflect the overflow pollution control level, and the calculation formula is: overflow pollution control facility reduction volume ÷ overflow volume without control facilities × 100%.

[0103] For the standard treatment rate of sewage and wastewater, standard treatment of sewage and wastewater is the most basic requirement for efficient operation of urban sewage treatment plants. Therefore, the annual standard operation days of sewage treatment plants are used to reflect the sewage treatment efficiency, and the calculation formula is: sewage treatment plant standard days ÷ total days of sewage treatment plant standard operation evaluation, wherein the daily average emission value of pollutants such as Cr2O7-2 index (COD Cr ), BOD5, suspended solids (SS), ammonia nitrogen (NH3-N), total nitrogen (TN), and total phosphorus (TP) meet the corresponding sewage treatment plant design effluent standard, and if one item does not meet the standard, it is considered as one day of non-compliance.

[0104] For the additional reduction rate of sewage plant pollution load, the additional reduction of sewage plant pollution load is to evaluate the additional reduction of pollutants exceeding the design effluent standard to guide the development of urban water environment governance to a higher level. By reducing the pollution load of sewage treatment plants, a higher water environment capacity is provided for urban economic development. At the same time, due to the serious eutrophication problem caused by NH3-N and TP exceeding the standard in river and lake water bodies, only the additional reduction rates of NH3-N and TP pollution load are considered. The calculation formula is: NH3-N pollution load additional reduction rate × 0.75 + TP pollution load additional reduction rate × 0.25, wherein, NH3-N / TP pollution load additional reduction rate = (sewage treatment plant actual pollution load reduction amount - sewage treatment plant design pollution load reduction amount) / sewage treatment plant design pollution load reduction amount × 100%; sewage treatment plant actual pollution load reduction amount is calculated according to the actual inflow and outflow water quality and treatment water quantity; sewage treatment plant design pollution load reduction amount is calculated according to the design inflow and outflow water quality and treatment water quantity; 0.75 and 0.25 represent the additional reduction indexes of NH3-N and TP, which are determined in combination with the pollution equivalent of NH3-N and TP.

[0105] For the water quality of water function area, the water quality of natural water bodies such as rivers and lakes directly reflects the treatment effect of urban water environment, so the treatment effect is evaluated by calculating the water quality of water function area. The calculation formula is: the number of water function areas meeting the standard ÷ the total number of water function areas included in the evaluation range × 100%, the evaluation of water quality includes the basic content of "Surface Water Environmental Quality Standard", including dissolved oxygen (DO), pH, COD, NH3-N, TP and other indicators. In a single monitoring process, all indicators meet the corresponding standard, and the water quality of water function area is qualified.

[0106] For the water body eutrophication index, river and lake water body eutrophication is a common problem, so the effectiveness of urban water body treatment is reflected by calculating the eutrophication index. The calculation formula is: the eutrophication index of each river and lake ÷ the total number of rivers and lakes participating in evaluation, TLI represents the eutrophication index of a single water body, W j The correlation weight of the nutritional status index of the jth parameter, n is the number of parameters, TLI j represents the nutritional status index of the jth parameter, and the parameters include chlorophyll a (Chla), TP, TN, transparency (SD) and permanganate index (COD Mn ).

[0107] In terms of water ecology, for the ecological shoreline rate, ecological shoreline can resist wave, water flow invasion and erosion and cause bank slope collapse under the action of soil pressure and groundwater seepage pressure, thereby maintaining plant growth, animal habitat, and water and soil integration. It includes natural shoreline and ecological revetment, so the proportion of natural shoreline and ecological revetment to the total length of river and lake shoreline is used to evaluate the habitat condition. The calculation formula is: the length of river and lake ecological shoreline (km) ÷ the total length of river and lake shoreline (km) × 100%.

[0108] For the river curvature, the river curvature can reflect the influence of high-intensity human activity disturbance on river system morphology, structure and function, and further affect the biological habitat and biodiversity of the basin, and can reflect the natural ecological background of the river. The calculation formula is: the actual length of the river ÷ the straight line length between the starting point of the river.

[0109] For the diversity index of benthic macroinvertebrates, the evaluation of river and lake water body biodiversity covers submerged plants, emergent plants, plankton, fish, birds and other species. The diversity index of each species can reflect the biodiversity level of the water system to a certain extent. The diversity index of indicator species can reflect the overall level of biodiversity, so the diversity index of benthic macroinvertebrates is used to reflect the biodiversity of water body. The Shannon-Wiener diversity index is used as the evaluation standard, and the calculation formula is: wherein P i Pi represents the proportion of the number of individuals of species i in the total number of individuals, and n represents the species abundance.

[0110] S205, obtaining a plurality of difficulty factors corresponding to each second dimension of the second dimension set, the difficulty factor being used to indicate the analysis difficulty of the second dimension; for each second dimension, deleting the maximum value and the minimum value in the plurality of difficulty factors corresponding to the second dimension, and determining the average difficulty factor of the second dimension set according to the average value of the plurality of difficulty factors of each second dimension; when the average difficulty factor of the second dimension set is greater than a preset difficulty factor threshold, adjusting the analysis strategy of each second dimension of the second dimension set.

[0111] Specifically, the difficulty factor can be evaluated and valued by a plurality of experts, and can be divided into 1, 2, 3, and 4 levels, representing easy, relatively easy, relatively difficult, and difficult, respectively. After deleting the maximum value and the minimum value in the plurality of difficulty factors corresponding to each dimension, the average value D i Then, the average difficulty factor is calculated, and the specific calculation formula is as follows:

[0112] In the formula: is the average difficulty factor, D i is the difficulty factor of the i-th second dimension, which is used to represent the difficulty of the i-th second dimension in monitoring, calculation, and evaluation, and n is the number of second dimensions in the second dimension set.

[0113] The preset difficulty factor threshold value is determined according to the actual situation, and can be 1.5. Here, it is taken as an example. If it represents relatively easy analysis, which is suitable for the analysis of the system management effect of urban water environment; if it represents relatively difficult analysis, and the analysis strategy of the related second dimension of the second dimension set is adjusted, and the evaluation content and method are optimized until

[0114] S206, when the comprehensive effectiveness degree is greater than or equal to the preset effectiveness threshold value and the stability degree is greater than or equal to the preset stability threshold value, analyzing the system management effect of urban water environment according to the second dimension set to obtain the management effect analysis result.

[0115] When the comprehensive effectiveness degree and the stability degree meet the conditions, the urban water environment management effect is quantitatively calculated, including water environment system element investigation, water environment element evaluation, and water environment management effect analysis.

[0116] The water environment system element investigation is to combine the dimension calculation formula, and use methods such as field investigation method and model simulation method to monitor, investigate, and calculate the water-related element status corresponding to the dimension.

[0117] In terms of water resources, the actual construction standards and design standards of urban flood control projects are investigated and analyzed for the compliance rate of urban flood control projects. Among them, the design standard refers to the Urban Flood Control Specification and the Design Standard for Urban Flood Control Projects.

[0118] In terms of urban drainage compliance area, the standards and regional locations of drainage tasks are investigated and determined. The relevant software is used to calculate the area, combined with the drainage situation during the rainy season to analyze the area that meets the drainage standards, and the relevant software is used to calculate the compliance area. When there is no standard for drainage compliance, refer to the Outdoor Drainage Design Standard and the Design Standard for Urban Flood Control Projects.

[0119] In terms of rainwater runoff pollution load reduction rate, the infiltration volume, infiltration coefficient, hydraulic slope, and effective infiltration area of facilities with runoff infiltration function are calculated, and the rainfall, average concentration of suspended pollutants in runoff pollution, and average concentration of suspended pollutants in facility effluent are monitored and calculated.

[0120] In terms of key river and lake ecological flow compliance rate, the daily average flow of key rivers and lakes in the past year is investigated in combination with hydrological station data.

[0121] In terms of water system connectivity, the river network is generalized using a model, and the number of river chains and nodes in the river network is calculated.

[0122] In terms of water environment, for the health of the drainage network, randomly select one-tenth of the length of the urban drainage network, and combine the detection results of the past year to calculate the degree and number of structural defects (cracks, deformation, corrosion, misalignment, undulation, disconnection, interface material shedding, branch pipe dark connection, foreign matter insertion, leakage) and functional defects (sedimentation, scaling, obstacles, wall / barrage root, tree roots, dregs).

[0123] In terms of centralized collection rate of urban domestic sewage, the influent quantity of sewage treatment plants, BOD5 concentration of influent water of sewage treatment plants, daily BOD5 discharge per capita, and population of the area receiving sewage treatment plants are monitored and calculated.

[0124] In terms of annual overflow volume control rate, continuous rainfall monitoring data with a step of 1 minute or 5 minutes or 1 hour in the past 10 years is obtained from meteorological stations, and geographic information system (GIS) data such as source reduction facility parameters, network topology, interception trunk, underlying surface, and terrain are obtained. The Storm Water Management Model (SWMM) is used to generalize the area network and simulate and analyze the overflow volume during rainfall with or without overflow facilities.

[0125] For the standard treatment rate of sewage, the standard days of sewage treatment plant drainage in the block are calculated, and the daily average emission value of pollutants COD Cr , BOD5, SS, NH3-N, TN, TP meets the corresponding sewage treatment plant design effluent standard, which is the daily standard, and one item is not up to standard, which is identified as one day not up to standard.

[0126] For the additional reduction rate of sewage plant pollution load, the NH3-N and TP concentrations of urban domestic sewage treatment plant effluent are compared with the design effluent quality, and the additional reduction of NH3-N and TP load of sewage treatment plant based on the design effluent quality is calculated combined with the treatment water quantity.

[0127] For the water quality standard reaching rate of rivers, lakes and water function areas, the permanganate index and ammonia nitrogen index of important water function areas in the city are monitored once a month, and 12 times are continuously monitored. Among them, the research objects are all water function areas included in the list of National Important Rivers, Lakes and Water Function Area Division (excluding pollution control areas without water quality targets).

[0128] For the water body eutrophication index, the nutritional status of urban lakes and reservoirs is monitored once a month, and 12 times are continuously monitored. The monitoring indicators include chla, TP, TN, SD, COD Mn .

[0129] In terms of water ecology, for the ecological shoreline rate, the total length of urban river and lake ecological shoreline is investigated and calculated. Among them, the ecological shoreline includes natural shoreline and ecological revetment. Natural shoreline refers to natural undeveloped shoreline or shoreline that basically achieves the ecological function of shoreline through ecological restoration. Ecological revetment refers to the revetment facilities built to resist wave and water flow erosion and collapse of the bank slope caused by soil pressure and underground water seepage pressure, and to meet the requirements of plant growth, animal habitat, water and soil integration, etc.

[0130] For the river curvature, combined with the river network system diagram, the river network is generalized by using hydrodynamic model such as MIKE11 model, and the actual length of the river and the straight line length between the starting points of the river are investigated and calculated.

[0131] For the diversity index of benthic macroinvertebrates, biological sequencing is used to analyze the species of benthic macroinvertebrates in rivers and lakes, and the number of benthic macroinvertebrates is calculated.

[0132] Water environment system element analysis is based on the research of water environment system elements, combined with the evaluation method of each dimension, to calculate and analyze the treatment effect of water-related elements quantitatively.

[0133] For the dimension with good analysis situation, the management experience is summarized, such as perfect design, management system and proper operation and maintenance management; for the dimension with poor analysis situation, the correlation analysis method is used to analyze the related dimensions to judge the relevance, and combined with the field investigation and monitoring, the internal reasons causing the short board of the elements and the problem serious area are analyzed to provide ideas for improving the water environment quality.

[0134] S207, display the system management effect analysis result of the urban water environment.

[0135] S207 is similar to S105, and details are not repeated in the present embodiment.

[0136] The application provides a system management effect analysis method of urban water environment, which comprises the following steps: reading a first dimension set from a storage device, wherein the first dimension set comprises a plurality of first dimensions for analyzing the system management effect of the urban water environment; determining the test probability of each first dimension according to the analysis result of each first dimension for a plurality of cities, and determining the correlation degree between the analysis results of each two first dimensions, and screening a second dimension from the first dimension set according to the test probability of each first dimension and the correlation degree between the analysis results of each two first dimensions to form a second dimension set; determining the comprehensive effective degree of the second dimension set according to the difference between the preset analysis effect values of each second dimension, and determining the stability degree of the second dimension set according to the similarity between the analysis effect value of each second dimension and the target effect value; when the comprehensive effective degree is greater than or equal to a preset effective threshold value and the stability degree is greater than or equal to a preset stability threshold value, analyzing the system management effect of the urban water environment according to the second dimension set to obtain a management effect analysis result; and displaying the system management effect analysis result of the urban water environment. The application uses the test probability and the correlation degree to screen a plurality of dimensions for analyzing the system management effect of the urban water environment, and constructs a system management effect analysis method of the urban water environment, thereby solving the problem of how to objectively, scientifically and accurately analyze the system management effect of the urban water environment; the comprehensive effective degree and the stability degree of the second dimension set are determined to ensure the effectiveness and stability of the system management effect analysis of the urban water environment; the dimensions are used to analyze the water-related elements of the urban water environment, which helps the relevant departments to systematically understand the system management status and short board of the urban water environment.

[0137] The embodiments of the present application can divide the functional modules of the electronic device or the host device according to the above method examples. For example, each functional module can be divided according to each function, or two or more functions can be integrated in one processing unit. The integrated unit can be realized in the form of hardware or in the form of a software functional module. It should be noted that the division of the modules in the embodiments of the present application is illustrative, and is only a logical functional division. When actually implemented, another division manner can be used.

[0138] FIG. 3 is a structural schematic diagram of a system governance effect analysis device for urban water environment provided by an embodiment of the present application. As shown in FIG. 3, the system governance effect analysis device 400 for urban water environment includes a reading module 410, a screening module 420, a determination module 430, an analysis module 440, and a display module 450.

[0139] The reading module 410 is configured to read a first dimension set from a storage device, where the first dimension set includes a plurality of first dimensions for analyzing the system governance effect of urban water environment.

[0140] The screening module 420 is configured to determine a test probability of each first dimension according to the analysis results of a plurality of cities for each first dimension, determine a correlation degree between the analysis results of each two first dimensions, and screen a second dimension from the first dimension set according to the test probability of each first dimension and the correlation degree between the analysis results of each two first dimensions, to form a second dimension set.

[0141] The determination module 430 is configured to determine a comprehensive effective degree of the second dimension set according to a difference between the preset analysis effect values of each second dimension, and determine a stability degree of the second dimension set according to a similarity degree between the analysis effect value of each second dimension and a target effect value.

[0142] The analysis module 440 is configured to analyze the system governance effect of urban water environment according to the second dimension set when the comprehensive effective degree is greater than or equal to a preset effective threshold value and the stability degree is greater than or equal to a preset stability threshold value, to obtain a governance effect analysis result.

[0143] The display module 450 is configured to display the system governance effect analysis result of urban water environment.

[0144] Optionally, the screening module 420 is specifically configured to:

[0145] For each first dimension, the analysis result of the plurality of cities for the first dimension is determined. For each first dimension, the test probability of the first dimension is determined according to the corresponding analysis result of the plurality of cities for the first dimension.

[0146] Optionally, the screening module 420 is specifically configured to:

[0147] For each first dimension, an average of the analysis results corresponding to the plurality of cities for the first dimension is taken as an average analysis result for the first dimension; for any two first dimensions, the analysis results corresponding to the plurality of cities for the two first dimensions and the average analysis results for the two first dimensions are input into a Pearson correlation model to obtain a correlation degree between the analysis results for the two first dimensions.

[0148] Optionally, the screening module 420 is specifically configured to:

[0149] filtering, from the first dimension set, a first dimension with a test probability less than a preset test probability to obtain a second dimension set composed of at least one second dimension; and deleting one of each two second dimensions in the second dimension set with a correlation degree greater than or equal to a preset correlation degree.

[0150] Optionally, the determining module 430 is specifically configured to:

[0151] For each second dimension, an average analysis effect value of the second dimension is determined according to a plurality of analysis effect values corresponding to the second dimension; for each second dimension, an effective degree of the second dimension is determined according to the plurality of analysis effect values corresponding to the second dimension and the average analysis effect value of the second dimension; and a comprehensive effective degree of the second dimension set is determined according to the effective degrees of the second dimensions in the second dimension set.

[0152] Optionally, the determining module 430 is specifically configured to:

[0153] For each second dimension, an average analysis effect value of the second dimension is taken as a target effect value; and a stability degree of the second dimension set is determined according to a similarity degree between the analysis effect values corresponding to each second dimension and the target effect value of each second dimension.

[0154] Optionally, the analysis module 440 is specifically configured to:

[0155] When the comprehensive effective degree is less than a preset effective threshold and / or the stability degree is less than a preset stability threshold, the step of reading the first dimension set from the storage device is returned to.

[0156] Optionally, the analysis module 440 is specifically configured to:

[0157] Obtain a plurality of difficulty factors corresponding to each second dimension of the second dimension set, the difficulty factor being used to indicate the analysis difficulty of the second dimension; for each second dimension, after deleting the maximum value and the minimum value in the plurality of difficulty factors corresponding to the second dimension, determine the average difficulty factor of the second dimension set according to the average value of the plurality of difficulty factors of each second dimension; when the average difficulty factor of the second dimension set is greater than a preset difficulty factor threshold, adjust the analysis strategy of each second dimension of the second dimension set.

[0158] The embodiment provides a system management effect analysis device for urban water environment, which can execute the system management effect analysis method for urban water environment in the above embodiment, and has similar implementation principles and technical effects, which will not be described here again.

[0159] In the specific implementation of the system management effect analysis device for urban water environment, each module can be implemented as a processor, and the processor can execute computer execution instructions stored in the memory, so that the processor executes the system management effect analysis method for urban water environment.

[0160] FIG. 4 is a structural schematic diagram of an electronic device hardware provided by the embodiment. As shown in FIG. 4, the electronic device 500 includes at least one processor 510 and a memory 520. The electronic device 500 further includes a communication component 530. The processor 510, the memory 520 and the communication component 530 are connected through a bus 540.

[0161] In the specific implementation process, the at least one processor 510 executes computer execution instructions stored in the memory 520, so that the at least one processor 510 executes the system management effect analysis method for urban water environment as executed by the electronic device side.

[0162] The specific implementation process of the processor 510 can refer to the above method embodiments, which have similar implementation principles and technical effects, and will not be described here again.

[0163] In the above embodiment, it should be understood that the processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC) and the like. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor and the like. The steps of the disclosed method can be directly embodied as hardware processor execution or combined execution by hardware and software modules in the processor.

[0164] The memory can include a high-speed random-access memory (RAM) and can further include a non-volatile memory (NVM), such as at least one disk memory.

[0165] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus can be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, the bus in the drawings of the present application does not limit to only one bus or one type of bus.

[0166] The functions implemented by the electronic device and the master device described above are introduced for the scheme provided by the embodiments of the present application. It can be understood that the electronic device or the master device includes a hardware structure and / or a software module corresponding to each function in order to implement the above functions. The units and algorithm steps of each example described in combination with the embodiments disclosed in the embodiments of the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is implemented in hardware or computer software driven hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the technical solution of the embodiments of the present application.

[0167] The present application also provides a computer-readable storage medium, the computer-readable storage medium stores computer execution instructions, when the processor executes the computer execution instructions, for implementing the above-mentioned system management effect analysis method of urban water environment.

[0168] The readable storage medium described above can be any type of volatile or nonvolatile storage device or a combination implementation thereof, such as Static Random-Access Memory (SRAM), Electrically-Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special purpose computer.

[0169] An exemplary readable storage medium is coupled to the processor, thereby enabling the processor to read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a part of the processor. The processor and the readable storage medium can be located in an application-specific integrated circuit. Of course, the processor and the readable storage medium can also exist as discrete components in an electronic device or host device.

[0170] The present application also provides a computer program product, which comprises a computer program stored in a readable storage medium, and at least one processor of an electronic device can read the computer program from the readable storage medium, and the at least one processor executes the computer program to enable the electronic device to perform the scheme provided in any of the embodiments described above.

[0171] Those skilled in the art can understand that all or part of the steps of the above-mentioned method embodiments can be completed by program instruction related hardware. The foregoing program can be stored in a computer readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the foregoing storage medium includes ROM, RAM, magnetic disk or optical disk and various storage media that can store program codes.

[0172] So far, the technical solutions of the present application have been described in combination with the optional embodiments shown in the drawings, but those skilled in the art can easily understand that the protection scope of the present application is obviously not limited to these specific embodiments, and the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for analyzing the effect of systematic treatment of an urban water environment, characterized by, The method comprises: reading a first dimension set from a storage device, wherein the first dimension set comprises a plurality of first dimensions for analyzing system management effects of urban water environments; determining a test probability of each of the first dimensions according to analysis results of a plurality of cities for each of the first dimensions, and determining a correlation degree between analysis results of any two of the first dimensions, and screening a second dimension from the first dimension set according to the test probability of each of the first dimensions and the correlation degree between the analysis results of any two of the first dimensions to form a second dimension set; determining a comprehensive effective degree of the second dimension set according to a difference between preset analysis effect values of each of the second dimensions, and determining a stability degree of the second dimension set according to a similarity between the analysis effect value of each of the second dimensions and a target effect value; when the comprehensive effective degree is greater than or equal to a preset effective threshold and the stability degree is greater than or equal to a preset stability threshold, analyzing system management effects of the urban water environments according to the second dimension set to obtain management effect analysis results; displaying the management effect analysis results of the urban water environments.

2. The method of claim 1, wherein, The method comprises: for each of the first dimensions, determining analysis results of a plurality of cities for the first dimension; for each of the first dimensions, determining a test probability of the first dimension according to the analysis results of the plurality of cities corresponding to the first dimension.

3. The method of claim 2, wherein, The method comprises: for each of the first dimensions, taking an average value of the analysis results of the plurality of cities corresponding to the first dimension as an average analysis result of each of the first dimensions; for any two of the first dimensions, inputting the analysis results of the plurality of cities corresponding to the two first dimensions and the average analysis results of the two first dimensions into a Pearson correlation model to obtain a correlation degree between the analysis results of the two first dimensions.

4. The method of claim 1, wherein, The method comprises: screening the first dimension with the test probability less than a preset test probability from the first dimension set to obtain a second dimension set composed of at least one second dimension; deleting one of each of the two second dimensions with the correlation degree greater than or equal to a preset correlation degree in the second dimension set.

5. The method of claim 1, wherein, The method comprises: for each of the second dimensions, determining an average analysis effect value of the second dimension according to a plurality of analysis effect values corresponding to the second dimension; for each of the second dimensions, determining an effective degree of the second dimension according to the plurality of analysis effect values corresponding to the second dimension and the average analysis effect value of the second dimension; According to the effective degree of each second dimension in the second dimension set, a comprehensive effective degree of the second dimension set is determined.

6. The method of claim 5, wherein, The determining the stability degree of the second dimension set according to the similarity between the analysis effect value of each second dimension and the target effect value includes: For each second dimension, the average analysis effect value of the second dimension is taken as the target effect value; According to the similarity between the analysis effect value corresponding to each second dimension and the target effect value of each second dimension, the stability degree of the second dimension set is determined.

7. The method of claim 6, wherein, The stability degree of the second dimension set is determined according to the similarity degree between the analysis effect value and the target effect value of each second dimension by the following formula: wherein |p j ≤ 1, p j is the stability degree, n is the number of second dimensions in the second dimension set, x ij is the analysis effect value set by the jth expert for the ith second dimension, and yi is the average analysis effect value for the i-th second dimension, i yi is the average analysis effect value for the i-th second dimension, The average analysis effect value of each second dimension in the second dimension set is determined.

8. The method of claim 4, wherein, After the comprehensive effective degree of the second dimension set is determined according to the analysis effect value preset for each second dimension, and the stability degree of the second dimension set is determined according to the similarity between the analysis effect value of each second dimension and the target effect value, the method further includes: When the comprehensive effective degree is less than a preset effective threshold and / or the stability degree is less than a preset stability threshold, the step of reading the first dimension set from the storage device is returned.

9. The method of claim 8, wherein, Before the system governance effect of the urban water environment is analyzed according to the second dimension set to obtain the governance effect analysis result when the comprehensive effective degree is greater than or equal to the preset effective threshold and the stability degree is greater than or equal to the preset stability threshold, the method further includes: A plurality of difficulty factors corresponding to each second dimension of the second dimension set are obtained, and the difficulty factors are used to indicate the analysis difficulty of the second dimension; For each second dimension, after the maximum value and the minimum value in the plurality of difficulty factors corresponding to the second dimension are deleted, the average difficulty factor of the second dimension set is determined according to the average value of the plurality of difficulty factors of each second dimension; When the average difficulty factor of the second dimension set is greater than a preset difficulty factor threshold, the analysis strategy of each second dimension of the second dimension set is adjusted.

10. The method of claim 1, wherein, The determining the test probability of each first dimension according to the analysis result of each first dimension on a plurality of cities includes: According to the analysis result of each first dimension on a plurality of cities, the test probability of each first dimension is determined by a hypothesis testing method, the test probability is used to indicate the significance level of the first dimension, and the correlation degree between the analysis results of each two first dimensions is determined, and according to the test probability of each first dimension and the correlation degree between the analysis results of each two first dimensions, a second dimension is screened out from the first dimension set to form a second dimension set; The hypothesis testing method includes at least one of Z test, chi-square test, and Wald test; and the correlation degree is represented by a correlation coefficient.

11. A device for analyzing the systemic governance effect of urban water environment, characterized in that, The device includes: A reading module is configured to read a first dimension set from a storage device, wherein the first dimension set includes a plurality of first dimensions used for analyzing the system governance effect of the urban water environment; The reading module is configured to read a first dimension set from a storage device, wherein the first dimension set includes a plurality of first dimensions used for analyzing the system governance effect of the urban water environment; The screening module is configured to determine a test probability of each first dimension according to an analysis result of a plurality of cities in each first dimension, determine a correlation degree between analysis results of each two first dimensions, and screen a second dimension from the first dimension set according to the test probability of each first dimension and the correlation degree between the analysis results of each two first dimensions to form a second dimension set; The determining module is configured to determine a comprehensive effective degree of the second dimension set according to a difference between preset analysis effect values of each second dimension, and determine a stability degree of the second dimension set according to a similarity degree between an analysis effect value of each second dimension and a target effect value; The analysis module is configured to analyze a system governance effect of the urban water environment according to the second dimension set when the comprehensive effective degree is greater than or equal to a preset effective threshold and the stability degree is greater than or equal to a preset stability threshold, and obtain a governance effect analysis result. The display module is configured to display the governance effect analysis result of the urban water environment.

12. An electronic device, comprising: The processor and a memory connected with the processor in communication; The memory stores computer execution instructions; The processor executes the computer execution instructions stored in the memory to implement the method in any one of claims 1 to 10. The computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by the processor to implement the method in any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that, The computer program is executed by the processor to implement the method in any one of claims 1 to 10.

14. A computer program product, characterised in that, ​

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