CN115409318A - Natural-based water purification scheme optimization method integrating fuzzy AHP and MDS - Google Patents
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Abstract
The invention discloses a natural-based water purification scheme optimization method integrating fuzzy AHP and MDS, relating to the technical field of water, wastewater and sewage treatment and comprising the following steps: according to the characteristics of a water purification scheme based on nature, a criterion layer comprising environment, economy, ecology, management and technology and a plurality of evaluation indexes of a determined index layer are constructed, and actual data of the evaluation indexes are obtained; constructing a hierarchical framework comprising a target, the criterion layer, the index layer and a water purification scheme according to an analytic hierarchy process, and normalizing qualitative and quantitative indexes in the criterion layer by adopting a fuzzy matter element theory; constructing a judgment matrix according to an analytic hierarchy process, performing hierarchical sequencing on the criterion layer and the index layer by using the judgment matrix, and then performing consistency check, thereby outputting the synthesis weight of each index; the water purification schemes based on nature are ordered by a multidimensional scaling method and the optimal scheme is selected.
Description
Technical Field
The invention relates to the technical field of water, wastewater and sewage treatment, in particular to a natural-based water purification scheme optimization method integrating fuzzy AHP (analytic hierarchy process) and MDS (multidimensional scaling).
Background
The preferred methods currently used in water purification schemes are mainly the following: linear programming, dynamic programming, nonlinear programming, grey correlation analysis and analytic hierarchy process. However, these methods have disadvantages when the scheme is preferred.
The problems of the prior preferred method are as follows: the linear programming method, the dynamic programming method and the nonlinear programming method only consider the minimization of the cost and ignore other aspects, but the scheme with the minimum cost is not necessarily the optimal water purification scheme because environmental and ecological factors are also important, and the optimal water purification scheme is a scheme which comprehensively optimizes the cost, pollutant discharge, ecological environment and other factors; grey correlation analysis ignores the weight of judgment criteria and indexes, and the two factors are important bases for scheme optimization; the conventional analytic hierarchy process cannot integrate qualitative indexes when a scheme is optimized, and cannot classify schemes with similar advantages and disadvantages, so that the flexibility is insufficient.
The evaluation index of the existing water purification scheme is used for the natural-based water purification scheme, and the problems are as follows: the evaluation index of the existing water purification scheme cannot be used for a natural-based water purification scheme, which is one of natural-based solutions proposed by the International Union of natural preservation (International Union of Conservation Nature), aiming at dealing with global water pollution challenges by using the water purification function of some natural ecosystems. While the evaluation indexes of conventional water purification schemes (such as activated sludge process and A2/O process) generally include only cost (such as investment and operation cost) and pollutant purification efficiency, natural-based water purification schemes must consider many aspects such as hydrogeology, floor space and space availability in addition to the evaluation indexes of conventional water purification schemes.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a natural-based water purification scheme optimization method integrating fuzzy AHP and MDS, which comprises the steps of constructing a hierarchical framework based on the natural water purification scheme, constructing a judgment matrix by combining FME on the basis of AHP, sequencing the schemes by MDS, selecting the optimal natural-based water purification scheme, and further optimizing the schemes by combining correlation.
In order to achieve the purpose, the invention can adopt the following technical scheme:
a preferred method of integrating fuzzy AHP with MDS based natural water purification protocols comprising:
according to the characteristics of the water purification scheme based on the nature, a criterion layer comprising environment, economy, ecology, management and technology is constructed, and real evaluation index data of the water purification scheme based on the nature is collected;
constructing a hierarchical framework comprising a target, a criterion layer, an index layer and a water purification scheme according to an AHP analytic hierarchy process, and normalizing qualitative and quantitative indexes in the criterion layer by adopting an FME fuzzy matter element theory;
constructing a judgment matrix, performing consistency check through hierarchical sequencing and total hierarchical sequencing of the index layers, and outputting the synthesis weight of each index;
and sequencing the water purification schemes based on nature by adopting the relevance through MDS multi-dimensional scale, identifying similar schemes in the quality evaluation, and selecting the optimal scheme.
As a further technical scheme of the invention, the method comprises the following specific steps of constructing a hierarchical framework comprising a target, a criterion layer, an index layer and a water purification scheme according to an AHP (advanced analytic hierarchy process), and normalizing qualitative and quantitative indexes in the criterion layer by adopting an FME (fuzzy object element) fuzzy matter element theory:
firstly, under the environment, economy, ecology and management and technical rule layers, selecting characteristic indexes of all rules and constructing a hierarchical framework comprising a target, a rule layer, an index layer and a water purification scheme; simultaneously, adopting FME to construct fuzzy object elements as follows:
R＝(N,C,V)；
wherein R is fuzzy matter element, N is matter name, C is characteristic of matter, V is characteristic value of matter, and V includes fuzzy qualitative description.
For n-dimensional m fuzzy matter elements, constructing a composite fuzzy matter element as follows:
in the formula, R mn Is a composite fuzzy object element, N i Denotes the ith object (i =1, 2.., m), C k Denotes the kth feature (k =1, 2.., n), V ik Representing the kth characteristic value of the ith object.
Then, the indexes are normalized, and for the cost indexes, the normalization formula is as follows:
for environmental indicators, the normalization formula is:
in the formula of U ik Is the normalized index value, V ik Is the actual value of the index, minV ik Is the minimum value of the index, maxV ik Is the maximum value of the index.
And assigning a value to the qualitative index in the range of [0,1] according to the qualitative description.
The normalized composite fuzzy matter elements are as follows:
as a further technical solution of the present invention, the specific steps of constructing a determination matrix according to an AHP analytic hierarchy process, performing a consistency check through hierarchical ordering and total hierarchical ordering of index layers, and outputting a synthesis weight of each index include:
firstly, a judgment matrix is constructed according to an AHP analytic hierarchy process, and any index is compared with other indexes under the same criterion (a) ij ) As equally important, less important, moderately important +, highly important, highly important +, very important +, paramount, in [1,9 ]]Is given a weight within a natural number range ofImportance value, index of comparison, assignment a in reverse comparison ji ＝1/a ij Constructing an n × n dimensional matrix as:
the matrix a is multiplied by the weight W = (W1, W2.. Kon) of the vector, resulting in AW = nW, i.e.:
calculating the maximum eigenvalue lambda of the judgment matrix according to the judgment matrix max And then calculating a consistency index CI and an average random consistency index RI. The consistency index calculation formula is as follows:
the calculation formula of the one-time ratio CR of the total hierarchical ordering is as follows:
when CR is less than or equal to 0.1, the judgment matrix is acceptable, and when CR exceeds the limit value, the judgment matrix needs to be corrected.
After the consistency check is completed, the weight vector of each criterion relative to the target is obtained as follows:
in the formula (I), the compound is shown in the specification,
is the weight of the kth criterion Ck relative to the target.
Likewise, the weight vector for each index relative to the criteria is:
in the formula I s ，l s+1 ，...，l t (s.ltoreq.t.ltoreq.n) denotes the kth criterion C k Index of k The sequence numbers of the next first and last indexes.
Then, the synthesis weight W of each index with respect to the target is obtained as:
as a further technical scheme of the invention, the specific steps of sequencing water purification schemes based on nature by adopting the relevance through MDS multidimensional scale, identifying similar schemes in the quality evaluation and selecting the optimal scheme comprise:
firstly, the combination weight of each index and the normalized index value are used for calculating the relevance K of the index in each scheme j The calculation formula is as follows:
K j ＝W i ×U ji ；
in the formula, W i The composite weight of the i-th index is represented.
The Euclidean distance was then calculated as:
using Euclidean distance values to construct a matrix for MDS analysis, and taking the first two main components as feature vectors:
x(1)＝(E 11 ,，E 12 ，...，E 1k ，...，E 1N )′；
x(2)＝(E 21 ,，E 22 ，...，E 2N ，...，E 2N )′；
wherein x (1) and x (2) represent two features of Euclidean distance value matrixEigenvectors, E 1k 1 st eigenvector value, E, representing the kth solution in the Euclidean distance value matrix 2k The 2 nd eigenvector values of the kth scheme in the Euclidean distance value matrix are represented.
The dissimilarity between the correlations i and j is represented by δ ij Expressed, the ascending ordering is as follows:
at delta ij Is an independent variable and d ij And (4) using Shepard graph to check the MDS matching degree as a dependent variable, if points in the graph are distributed on a line 1. Based on d ij And delta ij To find d ij Fitting value of
Bond d ij And
calculating a pressure value
The formula is as follows:
in the formula (I), the compound is shown in the specification,
the minimum value of the pressure values is indicated,
it indicates that the principal component of MDS is optimal.
Computing a square root E for each solution's eigenvector values k ：
To E k In order of magnitude, i.e. order of merit of water purification scheme based on nature, E k The solution with the largest value is the optimal solution, and the MDS analysis can identify which solutions are similar in the goodness evaluation.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, the real evaluation index data based on the natural water purification scheme is collected, the hierarchical framework based on the natural water purification scheme is constructed, the judgment matrix is constructed on the basis of AHP in combination with FME, the schemes are sequenced through the hierarchical sequencing and the hierarchical total sequencing of the index layer, the consistency is checked and corrected, the schemes are sequenced through MDS, similar schemes in the quality evaluation are identified, the optimal natural water purification scheme is selected, and convenience is provided for a decision maker to flexibly select the final scheme when similar optimal schemes exist.
2. According to the method, weak links of different schemes can be identified through correlation comparison of indexes in different schemes, and suggestions are provided for optimization of different water purification schemes based on nature.
3. The invention mainly designs a set of complete, widely applicable and natural-based water purification scheme optimization method with objective and accurate evaluation result. The technology can cover the evaluation of each judgment criterion and index of the water purification scheme based on the nature, select the optimal water purification scheme based on the nature, identify the scheme with similar advantages and disadvantages, and provide convenience for a decision maker to flexibly select the final scheme. In addition, suggestions are provided for further optimization of different natural-based water purification schemes.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic illustration of the steps of a preferred method of a natural based water purification scheme according to an embodiment of the present invention;
FIG. 2 is a hierarchical framework diagram of a preferred method of a natural based water purification scheme according to an embodiment of the present invention;
FIG. 3 is a block diagram of a method for integrating fuzzy AHP and MDS in accordance with one embodiment of the present invention;
FIG. 4 is a schematic diagram of a decision matrix constructed based on the integrated fuzzy AHP and MDS methods according to an embodiment of the present invention;
FIG. 5 is a flowchart of the consistency check according to an embodiment of the invention;
FIG. 6 is a Shepard plot of verified MDS according to an embodiment of the present invention;
figure 7 is a graph of preferred results for MDS methods according to embodiments of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making any creative effort belong to the protection scope of the present application.
The embodiment is as follows:
it should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, of embodiments of the present invention are intended to cover non-exclusive inclusions, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements explicitly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It will be understood that the terms "central," "longitudinal," "transverse," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," "circumferential," and the like are used in an orientation or positional relationship indicated in the drawings for convenience and simplicity of description only and do not indicate or imply that the device or element so referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus should not be considered as limiting the invention.
In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless explicitly specified otherwise. Furthermore, unless expressly stated or limited otherwise, the terms "mounted," "connected," and "coupled" are to be construed broadly and encompass, for example, both fixed and removable coupling as well as integral coupling; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in a specific case to those of ordinary skill in the art.
In the present invention, unless otherwise expressly stated or limited, the first feature "on" or "under" the second feature may be directly contacting the first and second features or indirectly contacting the first and second features through an intermediate. Also, a first feature "on," "over," and "above" a second feature may be directly or diagonally above the second feature, or may simply indicate that the first feature is at a higher level than the second feature. A first feature "under," "beneath," and "under" a second feature may be directly under or obliquely under the second feature, or may simply mean that the first feature is at a lesser elevation than the second feature.
Referring to fig. 1 and 2, in an embodiment of the present invention, a preferred method of integrating a fuzzy AHP with MDS for a natural based water purification scheme comprises:
s1: according to the characteristics of the water purification scheme based on the nature, a criterion layer comprising environment, economy, ecology, management and technology is constructed, and real evaluation index data of the water purification scheme based on the nature is collected, and the method specifically comprises the following steps:
according to the characteristics of the water purification system based on nature, economy, environment, ecology, management and technology are selected as criteria.
Economic guidelines for water purification schemes typically include investment, operating and disposal costs. The water purification system based on nature can maintain the activity of microorganisms by using soil or plants, remove pollutants in sewage, has no treatment cost of chemical agents or culture activated sludge and the like, and therefore, the occupied land cost is listed as another economic factor besides investment and operation.
The environmental criterion considers the water quality index BOD of the general water purification system 5 In addition to COD, suspended Solids (SS), total nitrogen, total phosphorus and faecal coliform, hydrogeological factors are also considered, for example, a stabilization pond and an artificial wetland require site selection to be located outside a flood alluvial plain and at a place with a low gradient, and all water purification systems based on nature need to consider the influence of flood and landslide.
Ecological and management criteria consider that maintenance and occupation space can utilize the factor, and water purification system based on nature can not only purify sewage, can also provide green open space for local community, provides the habitat for wild animal, and consequently, occupation space is available to an important ecological index.
Technical guidelines are used to evaluate the operation of the regimen and the additional requirements, and the operation of some natural based water purification systems is affected by seasonal factors, such as slow infiltration and surface flood land treatment systems, thus taking seasonal effects as a technical indicator.
In addition, different water purification schemes based on nature have additional requirements, a stabilization pond and an artificial wetland require soil impermeability at the site or minimal permeability after the site selection treatment, a surface flood treatment system depends on perennial herbaceous plants, and other water purification schemes based on nature can select more plants.
As shown in table 1, table 1 lists the indices under each evaluation criterion.
TABLE 1 indices and their function under various evaluation criteria based on natural water purification protocols
In the implementation case, the index values of the adopted water purification schemes based on nature are all real data, and the actual data of the operation of each scheme is obtained from the literature, so that the accuracy and the authenticity of the implementation result can be ensured.
S2: the method comprises the following steps of constructing a hierarchical framework comprising a target, a criterion layer, an index layer and a water purification scheme according to an AHP (advanced high Performance analysis) analytic hierarchy process, and normalizing qualitative and quantitative indexes in the criterion layer by adopting an FME fuzzy matter element theory, wherein the method comprises the following specific steps of:
a hierarchical framework is constructed that includes a goal, a guideline layer, an index layer, and a water purification scheme, the goal being to maximize benefit. Not only is the optimal economic benefit achieved, but also the cost, environmental acceptability, eco-friendliness, etc., which are traded off optimally in many ways, the criteria and target layers have been detailed at S1, and the water purification schemes include rapid infiltration treatment systems, slow infiltration land treatment systems, surface flood land treatment systems, constructed wetlands, and stabilization lagoon treatment systems. As the indexes constructed in the embodiment comprise qualitative indexes and quantitative indexes, wherein the quantitative indexes comprise percentage indexes and synthetic indexes, different types of indexes have larger influence on the weight of constructing the analytic hierarchy process, and the index values are normalized to avoid adverse influence.
For the cost index, the normalization formula is:
for environmental indicators, the normalization formula is:
in the formula of U ik Is the normalized index value, V ik Is the actual value of the index, minV ik Is the minimum value of the index, maxV ik Is the maximum value of the index.
For qualitative indicators, values are assigned to the indicator in the range [0,1] according to the qualitative description.
As shown in fig. 3, a method block diagram for integrating the fuzzy AHP and MDS is shown, which is divided into the following steps for detailed description: establishing a hierarchical analysis framework, comparing indexes in pairs, weighting criteria and indexes, checking consistency, calculating correlation, calculating Euclidean distance matrix, establishing the relation between Euclidean distance and non-similarity, calculating pressure value, performing MDS analysis and selecting an optimal natural-based water purification scheme.
S3: constructing a judgment matrix according to an AHP analytic hierarchy process, performing consistency check through hierarchical sequencing of the index layers and total hierarchical sequencing, and outputting the synthesis weight of each index;
as shown in FIG. 4, the steps of constructing the judgment matrix are schematically illustrated, and the steps include comparing any index with other indexes under the same criterion according to the same importance, less importance, moderate importance +, high importance +, very importance, very important +, and extremely important, in [1,9 ]]Is given an importance value a within the range of natural numbers ij Index of comparison, valuation a in reverse comparison ji ＝1/a ij And constructing a final judgment matrix after all values are assigned.
In this embodiment, the environmental criteria are taken as an example, whichWithin the guideline is BOD 5 The removal rate, the COD removal rate, the suspended matter removal rate, the total nitrogen removal rate, the total phosphorus removal rate, the faecal coliform removal rate and the hydrogeological risk index. BOD of the seed 5 The removal rate is compared and assigned with the removal rate of self and COD, the removal rate of suspended matters, the removal rate of total nitrogen, the removal rate of total phosphorus, the removal rate of faecal coliform and the hydrogeological risk in turn to obtain:
in the formula, w 1 、w 2 、w 3 、w 4 、w 5 And w 6 According to importance in [1,9]The natural number is given to the inside of the container,
represents BOD 5 The importance of removal rate to itself and other indicators (i =1,2.., 6). In contrast, any other index is related to BOD 5 Importance of removal when comparing removal rates
Namely a i1 ＝1/a 1i . And analogizing in sequence, finally obtaining a matrix in which every two indexes under the environmental criterion are compared and assigned as elements, similarly constructing a matrix in which every two indexes under other criteria are compared and assigned as elements, and combining the matrixes constructed by the criteria to form a matrix A:
in this embodiment, the hierarchical ordering of the index layers is that for a certain criterion, the importance of each index under the criterion is weighted
And the expression is the characteristic vector of the index pairwise comparison matrix under the criterion. The importance of the same criteria is weighted by W C Expressed as a comparison matrix of each criterionThe feature vector of (2). The synthetic weight of each index relative to the target is:
in the formula I s ，l s+1 ，...，l t (s.ltoreq.t.ltoreq.n) denotes the kth criterion C k Index of k The sequence numbers of the next first and last indexes.
A times the weight of each criterion W = (W) 1 、W 2 ，...，W N ) ', the obtained judgment matrix AW is:
the specific steps for performing the consistency check in this embodiment are shown in fig. 5, and the specific steps include: calculating the maximum eigenvalue lambda of the judgment matrix max Calculating a consistency index CI, and calculating an average one-time ratio CR by combining the CI and the selected average random consistency index RI.
If CR is less than or equal to 0.1, pass the consistency check, if CR is greater than 0.1, fail the consistency check, and need to give weight to the criterion and index again.
The consistency index calculation formula is as follows:
according to the dimension c of the matrix, the average random consistency index RI is looked up according to Table 2.
TABLE 2 average random consistency index RI
The calculation formula of the one-time ratio CR of the total hierarchy ordering is as follows:
s4: and sequencing the water purification schemes based on nature by adopting the relevance through MDS multidimensional scale, identifying similar schemes in the quality evaluation, and selecting the optimal scheme.
Calculating the degree of correlation K of each index according to the combined weight of each index relative to the target and the normalized index value j ：
K j ＝W i ×U ji ；
In the formula, W i The combining weight, U, representing the ith index ji Is the normalized index value.
Calculating Euclidean distance d by using correlation degree ij Comprises the following steps:
using Euclidean distance values to construct a matrix for MDS analysis, and taking the first two principal components as feature vectors:
x(1)＝(E 11 ,，E 12 ，...，E 1k ，...，E 1N )′；
x(2)＝(E 21 ,，E 22 ，...，E 2N ，...，E 2N )′；
in the formula, x (1) and x (2) represent two eigenvectors of Euclidean distance value matrix, E 1k 1 st eigenvector value, E, representing the kth scheme in the Euclidean distance value matrix 2k The 2 nd eigenvector values of the kth scheme in the Euclidean distance value matrix are represented.
The dissimilarity between the correlations i and j is represented by δ ij Expressed, the ascending ordering is as follows:
at delta ij Is an independent variable and d ij As a dependent variable, shepard graph is used for checking the matching degree of MDS (as shown in FIG. 6), if the points in the graph are distributed on a line 1. Based on d ij And delta ij D is obtained from the relation of ij Fitting value of
Bond d ij And
calculating a pressure value
The formula is as follows:
in the formula (I), the compound is shown in the specification,
the minimum value of the pressure values is indicated,
the time represents that the principal component of MDS is optimal.
Computing a square root E for each solution's eigenvector values k ：
To E k In order of magnitude, i.e. the order of merit of a natural-based water purification scheme, E k The most significant solution is the optimal solution, while the MDS analysis can identify which solutions are similar in the goodness evaluation (see figure 7).
The preferred results of the MDS method are shown in the figure that P4 and P5 are similar, P1, P2 and P3 are similar, and P4 and P5 are superior to P1, P2 and P3.
For investment, operation cost, land occupation cost and BOD 5 The clearance, COD clearance, suspended solid clearance, total nitrogen clearance, total phosphorus clearance, excrement coliform group clearance, hydrogeology risk maintenance, occupation of land space available, seasonal influence and extra requirement, the index correlation of each scheme is respectively: p1-rapid percolation treatment system (0.3, 0.9,0.81,0.96,1.00, 0.38,0.33,0.3,0.9,0.5, 0.9), P2-slow percolation land treatment system (0.26, 0.7,0.13,1.00,0.99,0.72,0.78,1.00,0.93,0.5,0.7,0.9,0.5, 0.7) P3-earth surface flood land treatment system (0.16, 0.7,0.19,0.96,0.89, 0.96,0.73,1.00,0.5,0.9,0.7, 0.5), P4-constructed wetland (0.88, 0.9,0.88,0.81,0.9,0.84,1.00,0.53,0.72,0.9,0.7,0.5,0.9, 0.5) and P5-stabilization pond treatment system (1.00, 0.9,1.00,0.94,0.85,0.74,0.99,0.65,0.52,0.7,0.9,0.5, 0.7). Through comparison of index correlation degrees of all schemes, the correlation degree of P1 in investment, total phosphorus removal rate, fecal coliform bacteria removal rate and hydrogeological risk maintenance is low, and optimization is needed; p2 has low correlation degree on investment and land occupation cost and needs to be optimized; p3 has low correlation degree on investment and land occupation cost and needs to be optimized.
It should be noted that the focus of the present invention is not to acquire data, but to calculate the correlation degree based on the index synthesis weight and the normalized index value calculated by the AHP by combining the AHP and MDS methods, and then to sort the schemes by the MDS based on the correlation degree.
For the present invention, it is not a series of processing of data that is critical, but the preference that enables the original data to be used for the solution by the method of the present invention.
The beneficial effects of the invention include:
1. when a natural based water purification scheme is preferred, the process takes into account not only cost, but also environmental and ecological factors.
2. The method not only can optimize the schemes, but also can identify the schemes with similar advantages and disadvantages, and provides convenience for a decision maker to flexibly select the optimal scheme when a plurality of winning schemes appear.
3. Weak links of different schemes can be identified through the correlation comparison of indexes in the schemes, and suggestions are provided for the optimization of different water purification schemes based on nature.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Moreover, various embodiments or examples and features of various embodiments or examples described in this specification can be combined and combined by one skilled in the art without being mutually inconsistent.
The above embodiments are only for illustrating the technical concept and features of the present invention, and the purpose thereof is to enable those skilled in the art to understand the contents of the present invention and implement the present invention accordingly, and not to limit the protection scope of the present invention accordingly. All equivalent changes and modifications made according to the spirit of the present disclosure should be covered within the scope of the present disclosure.
Claims (5)
1. A natural based water purification protocol optimization method that integrates a fuzzy analytic hierarchy process with a multidimensional scaling process, comprising the steps of:
according to the characteristics of a water purification scheme based on nature, a criterion layer comprising environment, economy, ecology, management and technology and a plurality of evaluation indexes of a determined index layer are constructed, and actual data of the evaluation indexes are obtained;
constructing a hierarchical framework comprising a target, the criterion layer, the index layer and a water purification scheme according to an analytic hierarchy process, and normalizing qualitative and quantitative indexes in the criterion layer by adopting a fuzzy matter element theory;
constructing a judgment matrix according to an analytic hierarchy process, performing hierarchical sequencing on the criterion layer and the index layer by using the judgment matrix, and then performing consistency check, thereby outputting the synthesis weight of each index;
the natural based water purification protocols are ordered by a multidimensional scaling method and the optimal protocol is selected.
2. The natural based water purification scheme preferred method of claim 1, wherein said natural based water purification scheme is: a water purification scheme using soil or plants that can sustain the activity of microorganisms sufficient to remove contaminants from wastewater.
3. The natural based water purification scheme optimization method according to claim 1, wherein the specific steps of constructing a hierarchical framework according to an analytic hierarchy process and normalizing qualitative and quantitative indexes in the criterion layer by using fuzzy matter element theory are as follows:
under the environment, economy, ecology and management and technical rule layers, selecting characteristic indexes of all rules, and constructing a hierarchical framework comprising a target, a rule layer, an index layer and a water purification scheme;
simultaneously, adopting FME to construct fuzzy object elements as follows:
R＝(N,C,V)；
wherein R is fuzzy matter element, N is matter name, C is characteristic of matter, V is characteristic value of matter, and V includes fuzzy qualitative description;
for n-dimensional m fuzzy matter elements, constructing a composite fuzzy matter element as follows:
C 1 …C n
in the formula, R mn Is a compound blurMatter element, N i Denotes the ith object (i =1, 2.., m), C k Denotes the characteristic of the kth object (k =1, 2.., n), V ik Representing the kth characteristic value of the ith object;
then, the indexes are normalized, and for the cost indexes, the normalization formula is as follows:
for environmental indicators, the normalization formula is:
in the formula of U ik Is the normalized index value, V ik Is the actual value of the index, minV ik Is the minimum value of the index, maxV ik Is the maximum value of the index;
assigning a value to the qualitative index within the range of [0,1] according to the qualitative description;
the normalized composite fuzzy matter elements are as follows:
C 1 …C n
4. the natural based water purification scheme preferred method according to claim 1, wherein the specific steps of weighting the guideline layer, the index layer are as follows:
a judgment matrix is constructed according to an analytic hierarchy process, any index is compared with other indexes under the same criterion according to the same importance, less importance, moderate importance +, high importance +, very importance and very important, and the method is characterized in that 1,9]Is given an importance value a within the range of natural numbers ij Indexes of comparison, inverse ratioA more timely valuation ji ＝1/a ij Constructing an n × n dimensional matrix as:
matrix a multiplied by vector weight W = (W) 1 ，W 2 ，...，W n ) AW = nW was obtained, i.e.:
calculating the maximum eigenvalue lambda of the judgment matrix max And then calculating a consistency index CI and an average random consistency index RI.
The consistency index calculation formula is as follows:
the calculation formula of the one-time ratio CR of the total hierarchical ordering is as follows:
when CR is less than or equal to 0.1, the judgment matrix is acceptable, and when CR exceeds a limit value, the judgment matrix needs to be corrected;
after the consistency check is completed, the weight vector of each criterion relative to the target is obtained as follows:
in the formula (I), the compound is shown in the specification,
is the kth criterion C k Weight relative to target；
Likewise, the weight vector for each index relative to the criteria is:
in the formula I s ，l s+1 ，...，l t (s.ltoreq.t.ltoreq.n) denotes the kth criterion C k Index of k The serial numbers of the next first and last indexes;
then, a composite weight W of each index with respect to the target is obtained as:
5. the natural based water purification scheme optimization method of claim 1, wherein the correlation degree K of indexes in each scheme is first calculated using the synthesis weight of each index and normalized index value j The calculation formula is as follows:
K j ＝W i ×U ji ；
in the formula, W i A composite weight representing the ith index;
the Euclidean distance was then calculated using the correlation as:
using Euclidean distance values to construct a matrix for MDS analysis, and taking the first two principal components as feature vectors:
x(1)＝(E 11 ,，E 12 ，...，E 1k ，...，E 1N )′；
x(2)＝(E 21 ,，E 22 ，...，E 2N ，...，E 2N )′；
in the formula, x (1) and x (2) are shown inTwo eigenvectors representing a matrix of Euclidean distance values, E 1k 1 st eigenvector value, E, representing the kth scheme in the Euclidean distance value matrix 2k Representing the 2 nd eigenvector value of the kth scheme in the Euclidean distance value matrix;
the dissimilarity between the correlations i and j is represented by δ ij Expressed, the ascending order is as follows:
at delta ij Is an independent variable and d ij And (3) using Shepard graph to check the matching degree of the MDS as a dependent variable, wherein if points in the graph are distributed on or close to a line 1. Based on d ij And delta ij To find d ij Fitting value of (2)
Bond d ij And
calculating a pressure value
The formula is as follows:
in the formula (I), the compound is shown in the specification,
the minimum value of the pressure value is indicated,
the time represents that the main component of the MDS is optimal;
computing a square root E for each solution's eigenvector values k ：
To E k In order of magnitude, i.e. the order of merit of a natural-based water purification scheme, E k The most significant solution is the optimal solution, while the MDS analysis can identify which solutions are similar in the goodness evaluation.
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Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100318512A1 (en) * | 2009-06-16 | 2010-12-16 | Ludwig Lester F | Advanced geographic information system (gis) providing modeling, decision support, visualization, sonification, web interface, risk management, sensitivity analysis, sensor telemetry, field video, and field audio |
| US20150199358A1 (en) * | 2014-01-15 | 2015-07-16 | Massachusetts Institute Of Technology | System and Method For Providing Unidimensional Scale Extraction from a Multidimensional Entity |
| CN109711765A (en) * | 2018-11-29 | 2019-05-03 | 国家电网有限公司 | Distribution materials and equipment classification method based on Kraljic buying location model |
| CN111654855A (en) * | 2020-06-04 | 2020-09-11 | 河海大学常州校区 | Authority updating method in underwater wireless sensor network based on AHP |
| CN112650894A (en) * | 2020-12-30 | 2021-04-13 | 国网甘肃省电力公司营销服务中心 | Multidimensional analysis and diagnosis method for user electricity consumption behaviors based on combination of analytic hierarchy process and deep belief network |
| CN112802611A (en) * | 2021-02-04 | 2021-05-14 | 天博电子信息科技有限公司 | Visual area prevention and control method based on epidemic situation risk model |
| CN112837184A (en) * | 2021-02-22 | 2021-05-25 | 辽宁科技学院 | Project management system suitable for building engineering |
| CN112907058A (en) * | 2021-02-07 | 2021-06-04 | 中国人民解放军军事科学院国防工程研究院 | Decision evaluation method based on intuitive fuzzy network hierarchical analysis |
| CN114186787A (en) * | 2021-11-05 | 2022-03-15 | 中国市政工程华北设计研究总院有限公司 | Urban black and odorous water body remediation model evaluation method based on multi-level fuzzy analysis |
| CN114341987A (en) * | 2019-04-12 | 2022-04-12 | 塔塔咨询服务有限公司 | System and method for bioremediation of contaminants |
| CN114358601A (en) * | 2022-01-04 | 2022-04-15 | 国网山东省电力公司经济技术研究院 | Method and device for constructing multi-dimensional evaluation index system of multi-energy system |
| CN114358575A (en) * | 2021-12-30 | 2022-04-15 | 沈阳建筑大学 | Floor evaluation index weight analysis method based on analytic hierarchy process |
| CN114547452A (en) * | 2022-02-18 | 2022-05-27 | 中国联合网络通信有限公司湖南省分公司 | Grid management optimization method and system based on multi-dimensional portrait assessment |
| CN114580266A (en) * | 2022-01-17 | 2022-06-03 | 南方海洋科学与工程广东省实验室(广州) | Land-source pollutant intelligent comprehensive evaluation method and system |
-
2022
- 2022-07-22 CN CN202210867628.6A patent/CN115409318B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100318512A1 (en) * | 2009-06-16 | 2010-12-16 | Ludwig Lester F | Advanced geographic information system (gis) providing modeling, decision support, visualization, sonification, web interface, risk management, sensitivity analysis, sensor telemetry, field video, and field audio |
| US20150199358A1 (en) * | 2014-01-15 | 2015-07-16 | Massachusetts Institute Of Technology | System and Method For Providing Unidimensional Scale Extraction from a Multidimensional Entity |
| CN109711765A (en) * | 2018-11-29 | 2019-05-03 | 国家电网有限公司 | Distribution materials and equipment classification method based on Kraljic buying location model |
| CN114341987A (en) * | 2019-04-12 | 2022-04-12 | 塔塔咨询服务有限公司 | System and method for bioremediation of contaminants |
| CN111654855A (en) * | 2020-06-04 | 2020-09-11 | 河海大学常州校区 | Authority updating method in underwater wireless sensor network based on AHP |
| CN112650894A (en) * | 2020-12-30 | 2021-04-13 | 国网甘肃省电力公司营销服务中心 | Multidimensional analysis and diagnosis method for user electricity consumption behaviors based on combination of analytic hierarchy process and deep belief network |
| CN112802611A (en) * | 2021-02-04 | 2021-05-14 | 天博电子信息科技有限公司 | Visual area prevention and control method based on epidemic situation risk model |
| CN112907058A (en) * | 2021-02-07 | 2021-06-04 | 中国人民解放军军事科学院国防工程研究院 | Decision evaluation method based on intuitive fuzzy network hierarchical analysis |
| CN112837184A (en) * | 2021-02-22 | 2021-05-25 | 辽宁科技学院 | Project management system suitable for building engineering |
| CN114186787A (en) * | 2021-11-05 | 2022-03-15 | 中国市政工程华北设计研究总院有限公司 | Urban black and odorous water body remediation model evaluation method based on multi-level fuzzy analysis |
| CN114358575A (en) * | 2021-12-30 | 2022-04-15 | 沈阳建筑大学 | Floor evaluation index weight analysis method based on analytic hierarchy process |
| CN114358601A (en) * | 2022-01-04 | 2022-04-15 | 国网山东省电力公司经济技术研究院 | Method and device for constructing multi-dimensional evaluation index system of multi-energy system |
| CN114580266A (en) * | 2022-01-17 | 2022-06-03 | 南方海洋科学与工程广东省实验室(广州) | Land-source pollutant intelligent comprehensive evaluation method and system |
| CN114547452A (en) * | 2022-02-18 | 2022-05-27 | 中国联合网络通信有限公司湖南省分公司 | Grid management optimization method and system based on multi-dimensional portrait assessment |
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