CN113033997B - Urban water quality grade determining method, device and medium based on improved set pair analysis - Google Patents
Urban water quality grade determining method, device and medium based on improved set pair analysis Download PDFInfo
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Abstract
The invention provides a method for determining urban water quality grade based on improved set pair analysis, which comprises the following steps: s1, identifying risk factors affecting urban water quality, and establishing a water quality risk assessment model; s2, determining the water quality condition evaluation grade and the standard of each water quality evaluation index according to the standard specification of the urban water quality; s3, determining the weight of each evaluation index of the urban water quality by using a hierarchical analysis method based on the water quality risk assessment model established in the S1, and calculating the contact degree of each evaluation index by using an improved set analysis method; and S4, weighting and calculating the association degree of each evaluation index in the area obtained in the step S3 and the weight of each evaluation index to obtain the comprehensive association degree of each level, and taking the comprehensive association degree as the water quality level of the evaluation area. The invention also provides a device and a medium for determining the urban water quality grade based on the improved set pair analysis, which can enable the water quality grade determination to be more efficient and reasonable.
Description
Technical Field
The invention relates to the field of water resource environment, in particular to a method, a device and a medium for determining urban water quality grade based on improved set pair analysis.
Background
Water resources are critical to sustainable social development and natural systems. Developing a water resource sustainability risk assessment is the most important part of water resource sustainability management. Human activities, such as urban construction, industrial and agricultural practices, and natural processes including water and soil loss and climatic conditions, affect water resources. Since the 80 s of the 20 th century, the rapid development of Chinese cities has led to serious water environmental problems, especially in some extra large cities and their surrounding areas. To maintain the urban aquatic environment, governments invest a great deal of money in controlling water pollution. This takes into account not only water quality but also sediment, ecosystem and vegetation. Therefore, quantification of water quality risk is one of the most challenging problems in protecting aquatic environments, and is also an important premise for further developing water resource protection.
According to the existing literature for evaluating urban water classification at home and abroad, in the water quality determination classification evaluation, the wide application methods include an Analytic Hierarchy Process (AHP), a numerical simulation calculation method, a centralized analysis method (SPA) and the like. Wherein, the index factors for the water quality evaluation model are more and have randomness and uncertainty, and the analysis method is characterized by analyzing the difference between the evaluation sample and the corresponding evaluation standard, so the analysis method is more suitable for determining the water quality grade. In the case of using the AHP method, the weights of individual factors need to be determined by expert questionnaires, and there are two methods of expert questionnaires: the factors of Saath are compared one by one, and the 1-9 scale proposed by Lyu et al (Lyu, H.M., sun, W.J., shen, S.L., zhou, A. (2020) Risk assessment using a new consulting process in fuzzy AHP.journal of Construction Engineering and Management, ASCE,146 (3), 04019112.Http:// dx.doi.org/10.1061/(ASCE) CO.1943-7862.0001757). The expert questionnaire method of Lyu and the like can be used for determining the fuzzy number and can easily meet the consistency requirement of the judgment matrix.
According to the prior art document retrieval, the patent publication No. CN102789546B discloses a quantitative determination method of a reference lake based on the human disturbance intensity, and the disturbance degree of human activities on the lake water quality is evaluated by combining a hierarchical analysis method and a traditional comprehensive set analysis method. However, the existing set analysis methods all have a common problem: when the application set determines the risk level by the analysis method, whether the influence of the evaluation factors on the evaluation result is positive or negative needs to be determined in advance, and then a corresponding formula is selected for calculation, so that the evaluation method is complicated in steps, and the influence of subjective factors on the level evaluation needs to be determined due to the fact that the enthusiasm or the depolarization of the evaluation factors is increased.
Disclosure of Invention
Aiming at the defects of the existing set analysis method in determining the urban water quality risk level, the invention provides a method, a device and a medium for determining the urban water quality level based on the improved set analysis, so that the water quality level determination is more efficient and reasonable.
According to a first aspect of the present invention, there is provided a method of determining a city water quality level based on an improvement set pair analysis, comprising:
s1, identifying risk factors affecting urban water quality, and establishing a water quality risk assessment model;
s2, determining the water quality condition evaluation grade and the standard of each water quality evaluation index according to the standard specification of the urban water quality;
s3, determining the weight of each evaluation index of the urban water quality by using a hierarchical analysis method based on the water quality risk assessment model established in the S1, and calculating the contact degree of each evaluation index by using an improved set analysis method;
and S4, weighting and calculating the association degree of each evaluation index in the area obtained in the step S3 and the weight of each evaluation index to obtain the comprehensive association degree of each level, and taking the comprehensive association degree as the water quality level of the evaluation area.
Optionally, the S1 includes:
s11, identifying and classifying evaluation indexes affecting water quality, and collecting influence parameter data;
s12, establishing a risk assessment model for influencing water quality according to the collected influence parameter data, wherein the risk assessment model is an index model for urban water quality risk assessment, which is established by considering objective factors.
Optionally, in the step S3, determining weights of the evaluation indexes of the urban water quality by using a analytic hierarchy process includes:
1) Constructing a risk assessment judgment matrix A;
through the established water quality risk assessment model, a single-layer analytic hierarchy process is established, and all evaluation indexes are compared with each other to obtain relative importance a ij Forming a judgment matrix A; a, a ij Refers to the evaluation index R j And R is R i Comparing the obtained relative importance, and adopting a 1-9 degree standard method to analyze and evaluate; judging that the order n of the matrix A is consistent with the number of the evaluation indexes;
2) Solving for the evaluation index weight omega i I.e. solving the maximum characteristic root lambda of the judgment matrix A max Corresponding feature vector omega i ，ω i The calculation formula is shown as the formula:
wherein M is i The method comprises the steps of judging the n times square root of the element product of the ith row of a matrix A;
maximum eigenvalue lambda max Determined by the following formula:
3) Judging the matrix A to carry out consistency test;
the condition for judging whether the matrix A meets the consistency is that the consistency check index (CR) is smaller than or equal to 0.1, and the weight of each evaluation index is calculated to obtain a characteristic vector omega i Components of (2); if CR is greater than 0.1, the matrix is judged not to meet the consistency test requirement and needs to be reconstructed.Specifically, CR is determined by formula 3):
wherein lambda is max Judging the maximum eigenvalue of the matrix; n is the order of the judgment matrix; RI is the random consistency coefficient of the judgment matrix, and is obtained through table lookup.
Alternatively, a ij Elements located in the ith row, jth column, and a of the judgment matrix ij ×a ji =1, and the construction judgment matrix is a= (a) ij ) 8*8 。
Optionally, in S3, calculating the association degree of each evaluation index by using an improved set analysis method includes:
improving the existing set analysis method based on the interval fuzzy number, and expressing the degree of connection by using the absolute value of the distance between the actual value and the corresponding calculation criterion; calculating the degree of association between the evaluation index and the evaluation grade standard of the urban water area quality; wherein, the liquid crystal display device comprises a liquid crystal display device,
the interval fuzzy number is an interval on a coordinate axis and consists of intermediate values of two adjacent standard values in the index evaluation grading standard;
the relation degree is represented by a segmented interval, the relation degree is calibrated through a relation degree function, and the relation degree obtained after calibration is a relative distance.
Optionally, the contact degree function has the following specific formula:
wherein, gamma m Alpha is less than or equal to gamma as a multiple contact degree function m ≤β；k m-1 ，k m ，k m+1 ，k m+2 Respectively evaluating the grading standards of the grade M; l (L) m-1 ，l m ，l m+1 Respectively (k) m-1 ,k m ),(k m ,k m+1 )，(k m+1 ,k m+2 ) Intermediate values of (2), namely:
optionally, in S4, the integrated association degree is calculated by the following formula:
wherein, gamma jm Refers to a single degree of association of index factors at the class M classification level; w (w) j A weight vector for each evaluation index; gamma ray pm For the comprehensive degree of association of all index factors under the classification level, 0 is less than or equal to gamma pm Less than or equal to 1, and calculating the comprehensive association degree gamma of each classification level M pm The closer its value is to 1, the closer the classification level of the region is to the M level.
Optionally, determining the grade of the urban water quality according to the comprehensive association degree and the maximum membership principle.
According to a second aspect of the present invention there is provided an apparatus for determining a grade of urban water quality based on an improvement set analysis, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterised in that the processor is operable to perform the method as described above when executing the program.
According to a third aspect of the present invention there is provided a computer readable storage medium having stored thereon a computer program which when executed by a processor is operable to perform the method described above.
Compared with the prior art, the invention has at least one of the following beneficial effects:
according to the method, the device and the medium, the risk assessment is carried out based on the water quality influence factors, the analytic hierarchy process and the centralized analytic hierarchy process are comprehensively adopted, the subjective and objective combination is realized, the ambiguity and the uncertainty of the risk assessment are considered, the problem of the complex uncertainty of the index in the assessment model can be effectively solved, and the accuracy of the risk assessment is improved.
The method, the device and the medium improve the set analysis method without judging the index type, simplify the original set analysis method, improve the safety and the stability of decision making, and provide a new method which is simpler, more convenient, more reasonable and more efficient for determining the water quality grade.
The method, the device and the medium of the invention propose an improved set analysis method which integrates the interval ambiguity into the traditional integrated set analysis method. The improved set expresses the degree of association by using the absolute value of the distance between the actual value of the sample and the evaluation standard value, and omits the step of judging the positive or negative influence of the evaluation index, so that the evaluation process is simpler, more convenient, more efficient and more reasonable.
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Other features, objects and advantages of the present invention will become more apparent upon reading of the detailed description of non-limiting embodiments, given with reference to the accompanying drawings in which:
FIG. 1 is a flow chart of a method for determining a city water quality level according to an embodiment of the present invention;
FIG. 2 is a schematic diagram showing the results of the analysis of water quality level determination by the improved set in accordance with one embodiment of the present invention;
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the present invention, but are not intended to limit the invention in any way. It should be noted that variations and modifications could be made by those skilled in the art without departing from the inventive concept. These are all within the scope of the present invention.
The embodiment of the invention provides a method for determining the urban water quality grade based on improvement set pair analysis, which combines a fuzzy analytic hierarchy process and an improvement set analytic process to determine water quality, performs analysis and calculation on related index parameters, and provides a novel method for determining the urban water quality grade. The method comprises the steps of identifying risk factors affecting urban water quality, and establishing a water quality risk assessment model; then, determining the water quality condition evaluation grade and the standard of each water quality evaluation index according to the standard specification of the urban water quality; determining the weight of each evaluation index of the urban water quality by using an analytic hierarchy process, and calculating the contact degree of each evaluation index by using an improved set analytic process; and finally, weighting the association degree of each evaluation index in the area and the index weight to obtain the comprehensive association degree of each level, and selecting the hierarchical comprehensive association degree closest to 1 as the water quality level of the evaluation area.
In a preferred embodiment of the invention, the accuracy of risk analysis is improved by combining a comprehensive analysis by layer Analysis (AHP) and an improved set analysis (SPA) through collecting basic parameters related to water quality, and the water quality grade determination is more efficient and reasonable by adopting the improved set analysis. Specifically, referring to fig. 1, a flowchart of a method according to a preferred embodiment of the present invention is shown, in which the method for determining the city water quality level based on the improvement set comprises the steps of:
and in the first step, index factors influencing water quality are identified and classified, and parameter data are collected.
In the step, the identification and classification of index factors influencing water quality refers to investigation and arrangement according to the information such as risk event of urban water quality and national water quality standard, and various factors directly influencing water quality can be identified and classified, and the index factors for evaluating water quality can be obtained after the factors are arranged.
Specifically, factors directly influencing water quality are as follows: population density, total domestic production per unit area, building area ratio, green area ratio, water per unit area, etc., and the selected factor index is determined by the actual condition of urban water environment.
Specific data affecting water quality index factors may be obtained through government official statistical websites evaluating cities, such as regional statistical offices, regional water resource authorities.
And secondly, establishing a risk assessment model affecting water quality.
In the step, the risk assessment model refers to an index model which is established by considering only objective factors and used for urban water quality risk assessment.
The risk assessment model aims to obtain the weight of each evaluation index on the influence of urban water quality. The evaluation index is a basic factor which directly affects the water quality, and the evaluation model is a single-layer index model.
And thirdly, determining the evaluation grade of the urban water quality and the grading standard of the evaluation index.
The urban water quality evaluation grade is classified into five categories of 1,2,3,4 and 5 according to the national standard specification GB3838-2002 'surface Water quality Standard'.
The grading standard of the evaluation index is determined by the following three aspects: (1) urban water quality standard established by the state or local government, (2) regional planning and development trend, and (3) the degree to which the selected evaluation factors are available, namely the grading standard of each index parameter of the engineering example.
In this embodiment, the classification level of the evaluation index is identical to the surface water area environment classification level, and is classified into five classes of 1,2,3,4 and 5.
Fourth, determining each index weight for evaluating the water quality by an analytic hierarchy process, specifically:
1) And constructing a risk assessment judgment matrix A.
Establishing a single-layer analytic hierarchy process by using the water quality risk assessment model established in the second step, and comparing each evaluation index with each other to obtain relative importance a ij A judgment matrix a is constructed. a, a ij Refers to the evaluation index S j And S is equal to i Comparing the relative importance, and adopting a 1-9 degree standard method to analyze and evaluate. For example, in one implementation, a ij Elements located in the ith row, jth column, and a of the judgment matrix ij ×a ji =1, and the construction judgment matrix is a= (a) ij ) 8*8 。
2) Solving for the evaluation index weight omega i 。
The process of solving the evaluation index weight is essentially to solve the maximum characteristic root lambda of the judgment matrix A max Corresponding feature vector omega i ，ω i The calculation formula is shown as a formula.
In formula 1), M i Is the nth root of the element product of the ith row of the judgment matrix A.
Maximum eigenvalue lambda max Can be determined by the following formula 2):
3) And (5) carrying out consistency test on the judgment matrix A.
The condition for judging whether the matrix A meets the consistency is that the consistency check index CR is smaller than or equal to 0.1, and the weight of each evaluation index is calculated as 1 to obtain a characteristic vector omega i Components of (2); if CR is greater than 0.1, the matrix is judged not to meet the consistency test requirement and needs to be reconstructed.
Fifthly, improving the existing set analysis method based on the interval fuzzy number, and calculating the degree of association between the evaluation index and the evaluation grade standard of the urban water area quality, specifically:
1) The existing set analysis method is improved based on the interval ambiguity.
Set analysis analyzes the identity, variability, and oppositivity of two related sets by establishing a correlation degree function that evaluates the correlation between the actual sample set and the evaluation criteria set. The objective of the set analysis method is to calculate the degree of association, which is essentially the distance between the actual sample value and the evaluation criterion value. The index types of the existing set analysis method are classified into smaller and more optimal types and larger and more optimal types. Therefore, before calculating the degree of contact using the correlation degree function, the index type needs to be judged in advance.
In this embodiment, the existing set analysis method is improved based on the interval ambiguity number, and the degree of association is expressed by the absolute value of the distance between the actual value and the corresponding calculation criterion. Therefore, the type of the evaluation index does not need to be determined in advance, the steps of the conventional set analysis method are simplified, and the safety and stability of evaluation are improved. The section fuzzy number is a section on the coordinate axis and consists of intermediate values of two adjacent standard values in the index evaluation grading standard. The relation degree is represented by a segmented interval, and is calibrated through a relation degree function formula, and the relation degree obtained after calibration is a relative distance.
2) The association degree function of the improved set analysis method is adopted, in this embodiment, α and β are respectively taken as 1 and 0, specifically:
wherein, gamma m Is a multi-element contact degree function; k (k) m-1 ，k m ，k m+1 Respectively evaluating the grading standards of the grade M; l (L) m-1 ，l m ，l m+1 Respectively (k) m-1 ,k m ),(k m ,k m+1 )，(k m+1 ,k m+2 ) Intermediate values of (2), namely:
and step six, according to the relation degree of the water quality evaluation indexes of the urban areas obtained by calculation in the step five, carrying out superposition calculation on the relation degree of the indexes and the corresponding weight occupied by the evaluation indexes obtained by the step four to obtain the comprehensive relation degree of the areas, thereby evaluating the risk grade of the areas.
The comprehensive association degree of the evaluation index is calculated by the following formula:
wherein, gamma jm Refers to a single degree of association of index factors at the class M classification level; w (w) j A weight vector for each evaluation index; gamma ray pm For the comprehensive degree of association of all index factors under the classification level, 0 is less than or equal to gamma pm Less than or equal to 1, and calculating the comprehensive association degree gamma of each classification level M pm The closer its value is to 1, the closer the classification level of the region is to the M level.
In this embodiment, the grade of the city water quality can be determined according to the comprehensive association degree and the maximum membership principle.
In another embodiment of the present invention, there is also provided a device for determining a city water quality level based on an improvement set-to-analysis, including a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor being operable to perform the above-described method for determining a city water quality level based on an improvement set-to-analysis when the program is executed.
In another embodiment of the present invention, there is also provided a computer readable storage medium having stored thereon a computer program which when executed by a processor is operable to perform the above-described method of determining urban water quality level based on a set of improvements versus analysis.
Specifically, in order to better illustrate the above technical solution of the present invention, the following provides specific application examples:
take Shanghai as an example. The Shanghai total occupied area is 6530 square kilometers, the resident population exceeds 2500 ten thousand, the resident population is located at 31 degrees 0'0' N,121 degrees 0'0' -122 degrees 0'0' E, and the resident population is the sea entrance of the Yangtze river and is surrounded by Hangzhou bay and east China sea. Due to geographical location, the surface water resources of Shanghai are quite abundant. Shanghai city is divided into sixteen administrative areas, xuehui, changning, jingan, putuo, hong kou, yangpu, huang Xu, bao shan, jiang, pudong, fengxian, jinshan, min Shengjiang, qing pu and Chong Ming island. According to statistics of Shanghai city water service bureau and Shanghai city administration in 2011, urban water resources mainly comprise 10 main rivers and 5 lakes. The water environment and the ecological system of the area are discharged with a large amount of sewage due to the development of industrial economy and the process of urban treatment; in addition, downstream of the Yangtze river at the Shanghai market, this makes it easier for contaminants in the Yangtze river basin to accumulate in the body of water there. Because surface water quality is one of the important factors affecting human health and safety of biological ecosystems, the quality of water resources owned by the surface water is of greater concern in addition to the total amount of water resources. Therefore, the water quality safety risk evaluation in Shanghai market has important significance. In the scheme, the city water quality grade determination method based on the improved set pair analysis method is adopted to evaluate and grade the Shanghai city water quality.
And the first step, identifying and classifying the evaluation indexes affecting the water quality, and collecting the data of the influencing parameters.
The evaluation indexes of the direct influence of the water quality in the embodiment are as follows: (1) population density (S) 1 Person/square kilometer), (2) average person domestic production total value (S) 2 Meta/person), (3) yield per unit area (S) 3 Thousands yuan per square kilometer), (4) building area ratio (S 4 ) (5) green area ratio (S) 5 ) (6) Water resource per capita (S) 6 Cubic meters per person). The present embodiment obtains water quality parameter data from the Shanghai statistical office and the Shanghai resource management office.
And secondly, establishing a risk assessment model affecting water quality.
The water quality risk assessment model is a single-layer risk assessment model composed of a target layer (water quality) and a factor layer (eight evaluation indexes listed in the first step).
And thirdly, determining the evaluation grade of the urban water quality and the grading standard of the evaluation factors.
The urban water quality evaluation grade of the embodiment is the same as the water quality classification in the national standard specification GB3838-2002 "quality Water quality Standard of surface Water Environment", and the specific situation is shown in Table 1.
TABLE 1 surface Water area environmental grade grading Standard
In this embodiment, specific grading evaluation criteria of the water quality evaluation factors of Shanghai city are formulated according to the national urban water quality standard, the regional planning and development trend of Shanghai city, the availability of statistical data of Shanghai city statistical bureau and water resource management bureau, as shown in the following table 2.
TABLE 2 surface Water quality evaluation factor grading Standard
Note that: s is S 1 ～S 6 With the basic parameters S in the first step 1 ～S 6 The meaning and units are consistent.
Fourth, determining the weight of each evaluation index by a hierarchical analysis method, specifically:
in the embodiment, 6 factors of the risk index model are compared with each other by adopting a 1-9 proportion scale method proposed by Lyu and the like to obtain a ij Constructing a pairwise judgment matrix A= (a) ij ) 6*6 . Calculating a feature vector corresponding to the maximum feature value of the matrix A, and obtaining a maximum feature value lambda max And carrying out consistency test on the judgment matrix.
In the present embodiment, the feature vector ω i Determined by formula 1), wherein the range of values of i is: i=1, 2, …,6; maximum eigenvalue lambda max Can be determined by equation 2), wherein the range of values of i and j: i, j=1, 2, …,6; lambda is set to max Substituted into formula 3), wherein ri=1.26 is found.
The calculation result of the embodiment is that the maximum eigenvalue lambda max The corresponding feature vector is omega i = (0.194,0.182,0.185,0.191,0.154,0.093), i.e. evaluation index: population density (person/km) 2 ，S 1 ) The total value (Yuan/ren, S) 2 ) Yield per unit area (10 billion yuan/km) 2 ，S 3 ) Building area ratio (S 4 ) Green area ratio (S 5 ) Water resource per capita (m) 3 Person, S 6 ) The weights corresponding to the weights are 0.194,0.182,0.185,0.191,0.154,0.093 respectively. Consistency test is carried out on the judgment matrix, and CR= 0.0336 is obtained through calculation<0.1, the consistency test passed, indicating that the judgment matrix was reasonable.
Fifthly, improving the existing set analysis method based on the interval fuzzy number, and calculating the degree of association between the evaluation index and the evaluation grade standard of the urban water area quality, specifically:
firstly, constructing a set analysis relation H, wherein water quality parameter data collected in the second step is an actual numerical value set A, and index evaluation standard sets B are formed by index parameter grading standards divided in the third step, so that a set pair H= (A, B) is constructed.
Next, in the present embodiment according to the third stepThe total of five levels (m=5) of the divided water quality levels are I e (k) for each of the evaluation indexes by generating the section fuzzy number using the standard parameters of each of the evaluation indexes 1 ,-∞)，II∈(k 1 ,k 2 )，III∈(k 2 ,k 3 )，IV∈(k 3 ,k 4 ) And V.epsilon.k 4 , + -infinity a) of the above-mentioned components, wherein the specific grading boundary value of each index parameter is k 1 ,k 2 ,k 3 ,k 4 See table 2 for the values of (a) and simultaneously calculate the intermediate value l between the two intervals by means of 5) m-1 ,l m ,l m+1 Taking m=3 as an example, specific examples are:
in this embodiment, the degree of association of each evaluation factor is defined as the interval distance, and the absolute value of the distance between the measured value of the index and the corresponding value in the evaluation criterion is calculated, so the calculated degree of association is the absolute value. 4) substituting the intermediate value l i And index boundary value k of each level i Can obtain the degree of association gamma of each level 1 (x),γ 2 (x),γ 3 (x),γ 4 (x) And gamma 5 (x)。
And step six, calculating the association degree of the water quality evaluation indexes of each area of the city, and carrying out superposition calculation on the association degree of each index and the weight occupied by the corresponding index to obtain the comprehensive association degree of each area, thereby evaluating the risk level of each area of the city.
In this embodiment, the evaluation index weight ω= (0.194,0.182,0.185,0.191,0.154,0.093) obtained by the fourth step is correlated with each evaluation index obtained by the fifth step 1 (x),γ 2 (x),γ 3 (x),γ 4 (x) And gamma 5 (x) Substituting into 6) to obtain the comprehensive association degree gamma of each region pk . Classification grade of urban area water quality is according to gamma pk The value of (2) is determined, the closer the value is to 1, the closer the classification level of the region is to the M level.
In the example, the classification of the water quality level of each region evaluated by the present method is shown in fig. 2. Wherein, chong is the best quality area 1 grade, pudong, partial hong kou, still, huang Pu, changning is the worst quality area 5 grade, baoshan, yangrong, putuo, xhui, min Shengzhu belongs to the quality of water 4 grade, pingjiang, jiang belongs to the quality of water 3 grade, qing Pu, jinshan, fengxian belongs to the quality of water grading 2 grade.
The water resource classification result determined by the improved set analysis method is compared with the actual water quality classification result of Shanghai city in 2017, and the classification calculated by the analysis of Qingdao, baoshan, hong kou, huangdao, yangdao, jingan, changning, xuehui, pingjiang and Min areas is basically consistent with the actual water quality classification. Wherein, chongming is 3 grades in the current grading, but the water quality of the water is consistent with the evaluation result because the water resource area for supplying water to Shanghai is surrounded by three water resource areas, namely Chongming water resource area, green grass sand water resource area and Chen Xing water resource area. In addition, the quality evaluation grading of the Jiang and Jinshan areas generated after the improvement is higher than that of the original set in the accuracy of the analysis method. The risk distribution result graph calculated by the improved set through the analysis method can be obtained, and the grade 4 of the water quality evaluation risk of the part of the areas of the Jiang mountain and the Jinshan is obviously higher than the grade 3 and grade 2 of the average water quality grade of the Jiang mountain. The two areas are respectively built with the Jiang automobile city and the Jinshan petrochemical plants, which shows that the water quality risk distribution accords with the actual situation and the risk grade of the local area is more accurate than that of the local area judged by the original set analysis method.
The foregoing describes specific embodiments of the present invention. It is to be understood that the invention is not limited to the particular embodiments described above, and that various changes and modifications may be made by one skilled in the art within the scope of the claims without affecting the spirit of the invention. The above-described preferred features may be used in any combination without collision.
Claims (6)
1. A method for determining a city water quality level based on an improvement set, comprising:
s1, identifying risk factors affecting urban water quality, and establishing a water quality risk assessment model;
s2, determining the evaluation grade of the urban water quality and the grading standard of the evaluation index according to the standard specification of the urban water quality;
s3, determining the weight of each evaluation index of the urban water quality by using a analytic hierarchy process based on the risk evaluation model established in the S1, and simultaneously, calculating the contact degree of each evaluation index in the area by using an improved set analytic process by combining the standard evaluation grading standard in the S2;
s4, weighting calculation is carried out on the contact degree of each evaluation index and the weight of each evaluation index in the area obtained in the S3, so that the comprehensive contact degree of each area is obtained, and the comprehensive contact degree is used as the grade for evaluating the water quality of the area;
in the step S3, the weight of each evaluation index of the urban water quality is determined by using an analytic hierarchy process, and the method comprises the following steps:
1) Constructing a risk assessment judgment matrix A;
through the established water quality risk assessment model, a single-layer analytic hierarchy process is established, and all evaluation indexes are compared with each other to obtain relative importance a ij Forming a judgment matrix A; a, a ij Refers to the evaluation index R j And R is R i Comparing the obtained relative importance, and adopting a 1-9 degree standard method to analyze and evaluate; judging that the order n of the matrix A is consistent with the number of the evaluation indexes;
2) Solving for the evaluation index weight omega i Said omega i To judge the maximum characteristic root lambda of matrix A max Corresponding feature vector omega i The calculation formula is shown as the formula:
wherein M is i The method comprises the steps of judging the n times square root of the element product of the ith row of a matrix A; a, a ij Is the element in the j-th column of the i-th row of the judgment matrix A;
maximum eigenvalue lambda max Determined by the following formula:
3) Judging the matrix A to carry out consistency test;
the condition for judging whether the matrix A meets the consistency is that the consistency check index CR is smaller than or equal to 0.1, and the weight of each evaluation index is calculated to obtain a characteristic vector omega i Components of (2); if CR is greater than 0.1, judging that the matrix does not meet the consistency test requirement, and reconstructing; specifically, the consistency check index CR is determined by:
wherein lambda is max Judging the maximum eigenvalue of the matrix A; n is the order of the judgment matrix A; RI is the random consistency coefficient of the judgment matrix A, and is obtained through table lookup;
in the step S3, calculating the degree of association of each evaluation index by using an improved set analysis method includes:
improving the existing set analysis method based on the interval fuzzy number, and expressing the degree of association by using the absolute value of the distance between the actual value and the corresponding calculation criterion; calculating the degree of association between the evaluation index and the evaluation grade standard of the urban water area quality; wherein, the liquid crystal display device comprises a liquid crystal display device,
the interval fuzzy number is an interval on a coordinate axis and consists of intermediate values of two adjacent standard values in the index evaluation grading standard;
the relation degree is represented by a segmented interval, and is calibrated through a relation degree function, and the relation degree obtained after calibration is a relative distance;
the specific formula of the contact degree function is as follows:
wherein, gamma m Alpha is less than or equal to gamma as a multiple contact degree function m ≤β；k m-1 ，k m ，k m+1 Respectively evaluating the grading standards of the grade M; l (L) m-1 ，l m ，l m+1 Respectively (k) m-1 ,k m ),(k m ,k m+1 )，(k m+1 ,k m+2 ) Intermediate values of (2), namely:
in S4, the comprehensive degree of contact is calculated by the following formula:
wherein, gamma im Refers to a single degree of association of index factors at the class M classification level; omega i A weight vector for each evaluation index; gamma ray pm For the comprehensive degree of association of all index factors under the classification level, 0 is less than or equal to gamma pm Less than or equal to 1, and calculating the comprehensive association degree gamma of each classification level M pm The closer its value is to 1, the closer the classification level of the region is to the M level.
2. The method for determining a city water quality level based on an improvement set versus analysis of claim 1, wherein S1 comprises:
s11, identifying and classifying evaluation indexes affecting water quality, and collecting influence parameter data;
s12, establishing a risk assessment model for influencing water quality according to the collected influence parameter data, wherein the risk assessment model is an index model for urban water quality risk assessment, which is established by considering objective factors.
3. The method for determining a city water quality level based on a set of improvement vs. analysis of claim 1, wherein a ij ×a ji ＝1，a ij A is the element positioned in the j-th column of the i-th row of the judgment matrix A ji For the elements located in the j-th row and i-th column of the judgment matrix, the judgment matrix is constructed as A= (a) ij ) 8*8 。
4. The method for determining the urban water quality grade based on the improvement set pair analysis according to claim 1, wherein the grade to which the urban water quality belongs is determined according to the comprehensive association degree and the maximum membership principle.
5. A device for determining urban water quality level based on an improved set of analysis, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor is operable to perform the method of any one of claims 1-4 when executing the program.
6. A computer readable storage medium having stored thereon a computer program, which when executed by a processor is operative to perform the method of any of claims 1-4.
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