CN112085375A - Selection method of vertical barrier scheme - Google Patents
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Abstract
The invention discloses a selection method of a vertical barrier scheme, which comprises the steps of determining evaluation factors through an expert evaluation system and establishing a multi-index and multi-level hierarchical structure; determining linguistic variables and corresponding simple triangular fuzzy numbers, triangular fuzzy numbers and reciprocal numbers through an expert evaluation system, and establishing a triangular fuzzy judgment matrix and a decision matrix; obtaining a weighted normalized triangular fuzzy decision matrix through triangular fuzzy analytic hierarchy process and fuzzy TOPSIS comprehensive application; and determining the distance between each scheme and the positive ideal point and the negative ideal point, and calculating the closeness, thereby selecting the optimal scheme of the vertical barrier. The method fills up the shortage of the selection method of the vertical obstructing barrier scheme in the relevant specifications, is simple and easy to operate, is beneficial to correct selection of the vertical obstructing barrier scheme by an engineer in the actual engineering, and reduces the obstructing engineering risk from the root.
Description
Technical Field
The invention relates to the field of environmental and geotechnical engineering, in particular to a selection method of a vertical barrier scheme.
Background
Vertical barrier barriers are an in-situ isolation technique by controlling the migration of contaminants in contaminated groundwater and soil in a contaminated site. There are many barrier types for vertical barrier barriers, such as a soil-bentonite vertical barrier, a soil-cement vertical barrier, a soil-cement-bentonite vertical barrier, a cement-bentonite vertical barrier, an alkali-activated slag-bentonite vertical barrier, and various geomembrane composite vertical barrier barriers, and the like. The performance indexes of the vertical separation barriers, such as seepage-proofing performance, strength characteristic, durability and the like, are different, and the requirements of different pollution sites on the vertical separation barriers are also different. Moreover, the problems of engineering cost, site condition requirements and secondary pollution are also the problems which need to be considered by engineers in the actual engineering. It can be seen that the selection of the vertical barrier scheme is a complex problem of multiple levels and factors.
However, in the existing specifications such as "vertical blocking technical standard in industrial pollution site" and the like, a method for selecting a vertical blocking barrier scheme is not clear enough, and in actual engineering, selection is only carried out by virtue of experts in a design institute according to experience, so that the method has strong subjectivity. Wrong selection of a vertical barrier scheme can cause great risks to actual barrier engineering, and great hidden dangers to the surrounding environment and human health and safety exist. Therefore, the reasonable selection method of the vertical barrier scheme is beneficial to filling up the blank of relevant specifications, is beneficial to correct selection of the scheme in actual engineering, and reduces the risk of barrier engineering from the root.
Disclosure of Invention
Aiming at the defects of the selection method technology of the existing vertical obstruction barrier scheme, the invention aims to provide a selection method of the vertical obstruction barrier scheme.
In order to solve the problems of the prior art, the invention adopts the technical scheme that:
a method for selecting a vertical barrier scheme comprises the following steps:
step 2, determining linguistic variables of a fuzzy analytic hierarchy process and linguistic variables of a fuzzy TOPSIS method, and respectively corresponding simple triangular fuzzy number, triangular fuzzy number and reciprocal;
step 3, collecting the expert opinions by adopting an expert opinion collection table-factor and an expert opinion collection table-scheme;
step 4, establishing simple triangle fuzzy judgment matrixes of each group according to the expert opinion collection table-factor in the step 3, the linguistic variable of the analytic hierarchy process in the step 2 and the corresponding triangle fuzzy number;
step 5, performing judgment matrix consistency check according to the formula (1), performing step 6 if the consistency index (CR) is less than 0.1, and otherwise, performing step 4 to collect new expert opinions again
In the formula (1), CI is a consistency index; RI is a random consistency index; lambda [ alpha ]maxJudging the maximum characteristic root of the matrix for the simple triangular fuzzy judgment; n is the order of the simple triangular fuzzy judgment matrix;
step 6, replacing the simple triangular fuzzy number in each grouping simple triangular fuzzy judgment matrix with a triangular fuzzy number, and establishing each grouping triangular fuzzy judgment matrix;
step 7, determining fuzzy integration degree S of each grouping triangular fuzzy judgment matrix according to the formula (2)iAnd linear weighting method is adopted to obtain final fuzzy integration degree of triangular fuzzy judgment matrix
In the formula (2), the reaction mixture is,
by
Calculating to obtain;
by
Calculating to obtain;
step 8, obtaining a triangular fuzzy decision matrix of each scheme according to the expert opinion collection table-scheme in the step 3, the linguistic variables of the fuzzy TOPSIS method in the step 2 and the corresponding triangular fuzzy number;
step 9, carrying out normalization processing on the triangular fuzzy decision matrix of each scheme according to the formula (3) and the formula (4);
in the formula (I), the compound is shown in the specification,
determining a matrix for the normalized triangular fuzzy;
the triangular fuzzy number in the decision matrix after normalization; x is the number ofijDetermining a triangular fuzzy number in the matrix;
by
Calculating to obtain;
step 10, establishing a weighted triangular fuzzy decision matrix according to the formula (5);
step 11, determining a positive ideal point and a negative ideal point according to the formulas (6) and (7), and determining the distance between each scheme and the positive ideal point and the negative ideal point according to the formulas (8) and (9)
In the formula, FPIS is a positive ideal point consisting of
Obtaining; FNIS is a negative ideal point consisting of
Obtaining;
the distance between each scheme and the positive ideal point;
the distance between each scheme and the negative ideal point;
step 12, determining the closeness of each scheme from the optimal scheme according to the formula (10), wherein the greater the closeness is, the more optimal the scheme is, and the optimal scheme of the vertical barrier is selected
In formula (10), CCiAnd i is a scheme number for the closeness of each scheme to the optimal scheme.
As an improvement, the linguistic variables of the fuzzy analytic hierarchy process in the step 2 are of equal importance, almost equal importance, importance between almost equal importance and slight importance, importance between slight importance, slight importance and Chinese medicine, importance between importance and very importance, importance between very importance and very important; simple triangular fuzzy numbers corresponding to the linguistic variables of the fuzzy analytic hierarchy process are 1,1 ', 2 ', 3 ', 4 ', 5 ', 6 ', 7 ', 8 ' and 9 '; the triangular fuzzy numbers corresponding to the linguistic variables of the fuzzy analytic hierarchy process are (1,1,1), (1,1,3), (1,2,4), (1,3,5), (2,4,6), (3,5,7), (4,6,8), (5,7,9), (6,8,10), (7,9, 11); the linguistic variables of the fuzzy TOPSIS method are very poor, normal, good and very good; the triangular blur numbers corresponding to the linguistic variables of the fuzzy TOPSIS method are (1,2,3), (2,3,4), (3,4,5), (4,5,6) and (5,7,9), and are specifically shown in Table 1 and Table 2.
As a modification, the importance of the factors in the step 3 is increased in the order of 1-2-3-4-5-6-7-8-9; the scheme comprises a soil-bentonite vertical barrier, a soil-cement-bentonite vertical barrier, a geomembrane vertical barrier and a GCL vertical barrier; the evaluation indexes of the scheme are very poor, general, good and very good. As an improvement, RI in step 5 takes a value: when n is 1, RI is 0, when n is 2, RI is 0, when n is 3, RI is 0.52, when n is 4, RI is 0.89, when n is 5, RI is 1.12, when n is 6, RI is 1.26, when n is 7, RI is 1.36, when n is 8, RI is 1.41, when n is 9, RI is 1.46, wherein n is the order number of the judgment matrix.
As an improvement, the distance in step 11 is obtained by the vertex method:
in the formula (11), the reaction mixture is,
and
are all triangular blur numbers.
The selection method of the vertical barrier scheme is applied to the selection of the barrier scheme in the environment and geotechnical engineering.
Has the advantages that:
compared with the prior art, the selection method of the vertical obstruction barrier scheme has the following advantages:
1) the selection of the vertical blocking barrier scheme is realized. Through the combined use of a novel expert questionnaire, a triangular fuzzy number, an analytic hierarchy process and a TOPSIS method, the selection of a vertical blocking barrier scheme is realized, the multi-factor and multi-level scheme selection of multiple experts is realized, the subjective prejudice of the individual experts is greatly reduced, the objectivity is provided, and the method radically improves the correctness of scheme selection compared with the traditional unilateral experience selection scheme of the experts.
2) The utility model provides a novel expert's questionnaire, for the questionnaire of two liang of comparisons of traditional analytic hierarchy process, this questionnaire has improved expert's work efficiency, has reduced the possibility that expert's individual bias exists, transfers a large amount of work load from the expert aspect to the analysts aspect.
3) The method fills the gap of the selection method of the vertical separation barrier scheme in the existing specification, is simple and practical, and is suitable for the engineer to select the scheme applied to the actual vertical separation engineering.
Drawings
Fig. 1 is a block diagram of a vertical barrier scheme selection procedure in example 1 of the present invention;
fig. 2 is a multi-index multi-level structure diagram in embodiment 1 of the present invention.
Detailed Description
The invention is further described with reference to specific examples.
Example 1
In the embodiment, a contaminated site of a certain biochemical limited company in sentence capacity city of Jiangsu province is taken as a background, and a vertical blocking barrier scheme of the site is selected by adopting the method disclosed by the invention, as shown in figure 1, the method comprises the following steps:
step 2, determining linguistic variables of a fuzzy analytic hierarchy process and linguistic variables of a fuzzy TOPSIS method, and respectively corresponding simple triangular fuzzy number, triangular fuzzy number and reciprocal as shown in tables 1 and 2;
TABLE 1 linguistic variables for the fuzzy analytic hierarchy process and corresponding simple triangular fuzzy numbers, triangular fuzzy numbers and reciprocal numbers
TABLE 2 linguistic variables for fuzzy TOPSIS method and corresponding triangular fuzzy numbers
| Linguistic variables | Triangular fuzzy number |
| Very poor | (1,2,3) |
| Difference (D) | (2,3,4) |
| In general | (3,4,5) |
| Good taste | (4,5,6) |
| Is very good | (5,7,9) |
Step 3, collecting the expert opinions by adopting an expert opinion collecting table-factor and an expert opinion collecting table-scheme, wherein eight expert opinions are shown in tables 3 and 4
TABLE 3 expert opinion Collection Table-factor feedback
Table 4 expert opinion Collection table-scheme feedback
And 4, establishing simple triangle fuzzy judgment matrixes of each group according to the expert opinion collection table-factor in the step 3, the linguistic variables of the analytic hierarchy process in the step 2 and the corresponding triangle fuzzy numbers, wherein the simple triangle fuzzy judgment matrixes are as follows:
the first group of simple triangular fuzzy judgment matrixes:
the second group of simple triangular fuzzy judgment matrixes:
a third group of simple triangular fuzzy judgment matrixes:
a fourth group of simple triangular fuzzy judgment matrixes:
step 5, performing judgment matrix consistency check according to the formula (1), performing step 6 if the consistency index (CR) is less than 0.1, and otherwise, performing step 4 to collect new expert opinions again;
in the formula (1), CI is a consistency index; RI is a random consistency index; lambda [ alpha ]maxJudging the maximum characteristic root of the matrix for the simple triangular fuzzy judgment; n is the order of the simple triangular fuzzy judgment matrix;
step 6, replacing the simple triangular fuzzy number in each group of simple triangular fuzzy judgment matrixes with a triangular fuzzy number, and establishing each group of triangular fuzzy judgment matrixes as follows:
TABLE 5 first set of decision matrices
TABLE 6 second set of decision matrices
| Factor(s) | A1 | A2 |
| A1 | (1,1,1) | (1,1,3) |
| A2 | (1/3,1,1) | (1,1,1) |
TABLE 7 third set of decision matrices
TABLE 8 fourth set of decision matrices
| Factor(s) | C1 | C2 |
| C1 | (1,1,1) | (1,2,4) |
| C2 | (1/4,1/2,1) | (1,1,1) |
Step 7, determining fuzzy integration degree S of each grouping triangular fuzzy judgment matrix according to the formula (2)iAnd a linear weighting method is adopted to obtain the final fuzzy integration degree of the triangular fuzzy judgment matrix, as shown in table 9:
in the formula (2), the reaction mixture is,
by
Calculating to obtain;
by
The result of the calculation is that,
TABLE 9 Final triangular fuzzy determination matrix fuzzy integration
| Factor(s) | Fuzzy integration degree (S)i) |
| A1 | (0.021,0.082,0.632) |
| A2 | (0.014,0.082,0.316) |
| B1 | (0.014,0.139,1.229) |
| B2 | (0.011,0.108,0.796) |
| B3 | (0.008,0.051,0.506) |
| B4 | (0.006,0.049,0.362) |
| B5 | (0.013,0.123,1.012) |
| C1 | (0.024,0.185,1.273) |
| C2 | (0.015,0.093,0.509) |
| D1 | (0.042,0.087,0.251) |
Step 8, obtaining a triangular fuzzy decision matrix of each scheme according to the expert opinion collection table-scheme in the step 3, the linguistic variables of the fuzzy TOPSIS method in the step 2 and the corresponding triangular fuzzy number, as shown in the table 10;
TABLE 10 triangular fuzzy decision matrix for each scheme
Step 9, carrying out normalization processing on the triangular fuzzy decision matrix of each scheme according to the formula (3) and the formula (4);
in the formula (I), the compound is shown in the specification,
determining a matrix for the normalized triangular fuzzy;
the triangular fuzzy number in the decision matrix after normalization; x is the number ofijDetermining a triangular fuzzy number in the matrix;
by
And (6) calculating.
Step 10, establishing a weighted triangular fuzzy decision matrix according to the formula (5), as shown in table 11;
TABLE 11 weighted triangular fuzzy decision matrix
Step 11, determine the positive and negative ideal points (FPIS and FNIS) according to equations (6) and (7), and determine the distance between each solution and the positive and negative ideal points according to equations (8) and (9), as shown in table 12.
In the formula, FPIS is a positive ideal point consisting of
Obtaining; FNIS is a negative ideal point consisting of
Obtaining;
the distance between each scheme and the positive ideal point;
the distance of each solution from the negative ideal point.
And step 12, determining the closeness of each scheme to the optimal scheme according to the formula (10), wherein the greater the closeness is, the better the scheme is, and selecting the optimal scheme of the vertical barrier, as shown in table 12, it can be seen that FMSB is the optimal scheme of the vertical barrier expansion of the polluted site.
In formula (10), CCiThe closeness of each scheme to the optimal scheme is determined.
TABLE 12 closeness of each case to the optimal case
In the embodiment, the influence of subjective factors of 8 experts is eliminated as much as possible, the vertical separation barrier scheme suitable for the site is objectively and reasonably selected from 4 alternative schemes by questionnaire survey collection of the 8 experts and data processing, and the design and construction of the vertical separation barrier project of the polluted site of a certain biochemical limited company in Jiangsu province and sentence-capacity city are guided.
The above description is only a preferred embodiment of the present invention, and the scope of the present invention is not limited thereto, and any simple modifications or equivalent substitutions of the technical solutions that can be obviously obtained by those skilled in the art within the technical scope of the present invention are within the scope of the present invention.
Claims (6)
1. A selection method of a vertical barrier scheme is characterized by comprising the following steps:
step 1, establishing an expert group, determining evaluation factors, carrying out layered grouping on factors affecting a vertical barrier, and establishing a multi-index and multi-level hierarchical structure; the expert group members are at least 5 persons;
step 2, determining linguistic variables of a fuzzy analytic hierarchy process and linguistic variables of a fuzzy TOPSIS method, and respectively corresponding simple triangular fuzzy number, triangular fuzzy number and reciprocal;
step 3, collecting the expert opinions by adopting an expert opinion collection table-factor and an expert opinion collection table-scheme;
step 4, establishing simple triangle fuzzy judgment matrixes of each group according to the expert opinion collection table-factor in the step 3, the linguistic variable of the analytic hierarchy process in the step 2 and the corresponding triangle fuzzy number;
step 5, performing judgment matrix consistency check according to the formula (1), performing step 6 if the consistency index (CR) is less than 0.1, and otherwise, performing step 4 to collect new expert opinions again
In the formula (1), CI is a consistency index; RI is a random consistency index; lambda [ alpha ]maxJudging the maximum characteristic root of the matrix for the simple triangular fuzzy judgment; n is the order of the simple triangular fuzzy judgment matrix;
step 6, replacing the simple triangular fuzzy number in each grouping simple triangular fuzzy judgment matrix with a triangular fuzzy number, and establishing each grouping triangular fuzzy judgment matrix;
step 7, determining fuzzy integration degree S of each grouping triangular fuzzy judgment matrix according to the formula (2)iAnd linear weighting method is adopted to obtain final fuzzy integration degree of triangular fuzzy judgment matrix
In the formula (2), the reaction mixture is,
by
Calculating to obtain;
by
Calculating to obtain;
step 8, obtaining a triangular fuzzy decision matrix of each scheme according to the expert opinion collection table-scheme in the step 3, the linguistic variables of the fuzzy TOPSIS method in the step 2 and the corresponding triangular fuzzy number;
step 9, normalizing the triangular fuzzy decision matrix of each scheme according to the formula (3) and the formula (4)
In the formula (I), the compound is shown in the specification,
determining a matrix for the normalized triangular fuzzy;
the triangular fuzzy number in the decision matrix after normalization; x is the number ofijDetermining a triangular fuzzy number in the matrix;
by
Calculating to obtain;
step 10, establishing a weighted triangular fuzzy decision matrix according to the formula (5)
Step 11, determining a positive ideal point and a negative ideal point according to the formulas (6) and (7), and determining the distance between each scheme and the positive ideal point and the negative ideal point according to the formulas (8) and (9)
In the formula, FPIS is a positive ideal point consisting of
Obtaining; FNIS is a negative ideal point consisting of
Obtaining;
the distance between each scheme and the positive ideal point;
the distance between each scheme and the negative ideal point;
step 12, determining the closeness of each scheme from the optimal scheme according to the formula (10), wherein the greater the closeness is, the more optimal the scheme is, and the optimal scheme of the vertical barrier is selected
In formula (10), CCiAnd i is a scheme number for the closeness of each scheme to the optimal scheme.
2. The method of selection of a vertical barrier scenario of claim 1, wherein linguistic variables of the fuzzy analytic hierarchy process in step 2 are of equal importance, almost equal importance, importance between almost equal importance and slight importance, importance between slight importance and importance, importance between importance and importance, very important; the simple triangular fuzzy numbers corresponding to the linguistic variables of the fuzzy analytic hierarchy process are respectively 1,1 ', 2 ', 3 ', 4 ', 5 ', 6 ', 7 ', 8 ' and 9 '; the triangular fuzzy numbers corresponding to the linguistic variables of the fuzzy analytic hierarchy process are respectively (1,1,1), (1,1,3), (1,2,4), (1,3,5), (2,4,6), (3,5,7), (4,6,8), (5,7,9), (6,8,10), (7,9, 11); the linguistic variables of the fuzzy TOPSIS method are very poor, normal, good and very good; the triangular fuzzy numbers corresponding to the linguistic variables of the fuzzy TOPSIS method are respectively (1,2,3), (2,3,4), (3,4,5), (4,5,6) and (5,7, 9).
3. The method of selecting a vertical barrier protocol according to claim 1 wherein the factors in step 3 increase in importance in order from 1-2-3-4-5-6-7-8-9; the scheme comprises a soil-bentonite vertical barrier, a soil-cement-bentonite vertical barrier, a geomembrane vertical barrier and a GCL vertical barrier; the evaluation indexes of the scheme are very poor, general, good and very good.
4. The selection method of a vertical barrier scheme according to claim 1, wherein the RI in step 5 takes the value: when n is 1, RI is 0, when n is 2, RI is 0, when n is 3, RI is 0.52, when n is 4, RI is 0.89, when n is 5, RI is 1.12, when n is 6, RI is 1.26, when n is 7, RI is 1.36, when n is 8, RI is 1.41, when n is 9, RI is 1.46, wherein n is the order number of the judgment matrix.
5. The method of selecting a vertical barrier solution according to claim 1, wherein the distance in step 11 is calculated using the vertex method:
in the formula (11), the reaction mixture is,
and
are all triangular blur numbers.
6. The application of the selection method of the vertical barrier scheme in the environmental and geotechnical engineering based on the claim 1 in selecting the barrier scheme.
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| CN113610337B (en) * | 2021-06-22 | 2024-04-19 | 中铁建华南建设有限公司 | Foundation pit engineering risk determination method, device, computer equipment and storage medium |
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