CN110097295A - The urgent technique recognition methods of sudden Water Basin Water Pollution accident, Decision System of Emergency - Google Patents
The urgent technique recognition methods of sudden Water Basin Water Pollution accident, Decision System of Emergency Download PDFInfo
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- 239000011159 matrix material Substances 0.000 description 4
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- 230000002776 aggregation Effects 0.000 description 2
- 238000004220 aggregation Methods 0.000 description 2
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Abstract
The present invention discloses a kind of urgent technique recognition methods of sudden Water Basin Water Pollution accident, Decision System of Emergency.Present invention firstly provides the decision weights measuring methods of distinguishing indexes, with similarity factor between Combination Rules of Evidence Theory introducing index evidence, the n group weight scoring that n experts the provide different distinguishing indexes group decision weights that permeate score, and solve the technical issues of weight conflicts between different expert analysis modes.The urgent technique recognition methods of the sudden Water Basin Water Pollution accident of the present invention improves optimizing decision quality by introducing above-mentioned decision weights measuring method.Two stage recognition method after this method optimization, can reduce operand, save the Emergency decision time.The Decision System of Emergency of the sudden Water Basin Water Pollution accident of the present invention, is divided into routine work and optimizing decision two parts for emergency response, can reduce the emergency response time under the premise of reducing expert's subjectivity opinions clash, realize Emergency decision truly.
Description
Technical field
The present invention relates to a kind of emergency response decision-making techniques of water pollution accident that happens suddenly, for identification more particularly to one kind
The method of the optimal emergency water pollution processing technique of sudden Water Basin Water Pollution accident belongs to water environment treatment, water pollution emergency
Response Decision technical field.
Background technique
Basin burst water pollution accident is mainly that pollutant by modes such as human production activity, pollutant discharge of enterprise enters water body
The water pollution problems of initiation is the most prominent type in outburst surroundings accident.According to statistics, in recent years in the outburst surroundings accident in China
94.7% belong to basin burst water pollution accident.Basin burst water pollution accident is unexpected with incident, pollution range is uncertain,
The features such as negative effect is big, processing disposition is arduous, thus the emergency response decision-making technic after basin burst water pollution accident occurs
It is particularly important.Among these again to identify that optimal processing technology is the core link of entire emergency response decision rapidly.
In the prior art, identify that optimal urgent technique substantially there are two class sides for basin burst water pollution accident
Case.The first kind is case match cognization scheme, is the similitude using history case and current pop-up threat, by current
The matching analysis of Accident Characteristic and case Accident Characteristic identifies current suitable treatment technology from case processing technique.Second class
It is expert analysis mode identifying schemes, is to be identified from existing processing technique on the basis of expert analysis mode according to current Accident Characteristic
Suitable treatment technology.In specific identification process, first by different experts on the basis of combining field condition feature to processing
The different distinguishing indexes of technology score, while also scoring different distinguishing indexes weights, then be calculated respectively by mathematical method
The final decision value of item distinguishing indexes, finally obtains the optimum identified on the basis of comprehensively considering different expertises
Emergency water pollution processing technique.Existing two classes identifying schemes all existing defects in actual operation, essentially consist in: for first
Class scheme, due to the diversity of valley environment and Accident Characteristic, thus current burst water pollution accident fears more difficult and case scenario,
The resolution of especially successful case matches.Especially for some rare water pollution types sent out less, existing case is more
To be limited, case matching method is almost difficult to carry out.For the second class scheme, expert analysis mode can preferably consider current accident
Each side's region feature also can select suitable treatment skill according to the thinking of science decision under the premise of independent of case technology
Art, but existing major defect is that the different experts problem larger to index weights assignment deviation can not be avoided.Especially locate
Usually there is the associations such as a degree of infiltration, interference between each distinguishing indexes of reason technology, this has more aggravated the weight as expert
When scoring conflict, how all expert opinions is scientifically integrated, identify the difficulty of optimum processing technique.Thus on the whole,
Compared to case match cognization scheme, the optimal urgent technique identifying schemes based on expert analysis mode have more advantages, but
Due to there is the relevance between identification and evaluation index, thus when different experts are larger to same index diversity of values, such as
What science, which solves the conflict between each expert opinion, becomes the critical problem of entire Emergency decision.
Summary of the invention
The purpose of the present invention is to the deficiencies in the prior art, a kind of the optimal of sudden Water Basin Water Pollution accident is provided
Urgent technique recognition methods, this method is on the basis of imposing expert analysis mode to alternative processing technique, with evidence theory
Is carried out to distinguishing indexes weight, and basic herein integrated the technical issues of assigning power, solving weight conflict between different expert analysis modes
On identify the optimal urgent technique of current water pollution accident.
To achieve the above object, present invention firstly provides a kind of decision weights measuring methods of distinguishing indexes, in root
During carrying out best techniques identification according to distinguishing indexes, different experts close the weight scoring of different distinguishing indexes
At obtaining the decision weights for final decision, its technical solution is as follows:
Different experts are subject to the weight scoring of different distinguishing indexes by a kind of decision weights measuring method of distinguishing indexes
Synthesis, obtains the decision weights for final decision;It is characterized by: implementing according to following steps:
Firstly, determining V (V >=5) item distinguishing indexes A;
Secondly, using expert point rating method, by n (n >=5) name expert respectively to the weight confidence score of V distinguishing indexes A,
Obtain n group weight evidence, V weight confidence score of the every group of weight evidence, that is, every expert to V distinguishing indexes A, every group of power
It lays emphasis on evidence and is denoted as weight evidence mp, p=1,2 ..., n;
Again, the similarity factor s between any two groups of weight evidences is calculated according to formula 1pq:
In formula, spq- any two groups of weight evidences mp、mqBetween similarity factor, mp、mq- weight evidence group mp, weight card
According to a group mq, determined by expert analysis mode, Ar、At- subset Ar, subset At, indicate any r-th, t-th distinguishing indexes A, Ak—
Subset Ar, subset AtIntersection,
mp(Ar)、mq(At)-respectively indicate weight evidence group mpMiddle distinguishing indexes ArWeight confidence score, weight evidence
Group mqMiddle distinguishing indexes AtWeight confidence score, determined by expert analysis mode;
Again, any weight evidence group m is calculated according to formula 2p, p=1,2 ..., the general branch that n is supported by remaining weight evidence group
Degree of holding μ (mp):
In formula, μ (mp)-any weight evidence group mpThe total support supported by remaining weight evidence group;
Again, any weight evidence group m is calculated according to formula 3pConfidence level λ (mp):
In formula, λ (mp)-any weight evidence group mpConfidence level;
Finally, calculating the decision weights ω (A of distinguishing indexes according to formula 4r):
In formula, ω (Ar)-any distinguishing indexes ArDecision weights.
The decision weights measuring method of above-mentioned distinguishing indexes is the weight reliability by n experts to different distinguishing indexes A
Distribution (i.e. n group weight scores) is integrated into one group of weight scoring, and referred to as decision weights score.This group of decision weights scoring effectively solution
The conflicting problem determined in distinguishing indexes quantizing process between each fused data, it is thus possible to improve it applied to final decision
Middle science.
The basic principle of the decision weights measuring method of above-mentioned distinguishing indexes is: in the decision-making process based on expert analysis mode
In, why need to use expert point rating method, it is not very complete often caused by the data of each index, determining each index weights
Shi Bixu is just able to achieve by the Subjective Knowledge experience of expert.And there are a degree of differences for the Subjective Knowledge experience of expert
Different, even for certain indexs, there are larger differences, thus cause to need in this kind of decision process to uncertain problem into
The technical issues of row scientific disposal.Decision weights measuring method of the present invention is the thought by evidence theory, by proposition (i.e. decision
Determination of the different experts to the weight of different distinguishing indexes in problem) uncertain problem conversion in order to gather (i.e. it is different specially
Family is to the trusting degree of subset each in framework of identification) uncertain problem, the weight confidence score of different experts is melted
It closes and redistributes, so that qualitative evaluation quantification is preferably utilized the weight brief combination based on similarity factor between evidence
Method solves the conflicting between each expert opinion.
Mathematical principle for the synthesis for identifying different weight reliabilities, above-mentioned decision weights measuring method is:
If Π is framework of identification, i.e., the set of each distinguishing indexes composition;Subset is AR, (r=1,2,3 ..., V)That is framework of identification
Any one of Π distinguishing indexes (subset herein refers both to single element subset, expert to the subset formed comprising multiple elements or
Empty set does not generate any trust distribution);m(Ar) indicate subset ArBasic trust partition function, i.e., expert is to ArTrust journey
Degree is presented as that weight scores.Items meet formula 6:
In above formula,Expression does not generate empty set any trust distribution,Indicate an expert
The sum of trusting degree value assigned to all subsets in framework of identification Π is 1.
If Π is the framework of identification comprising V index, subset is respectively Ar、At(r, t=1,2 ..., V), respectively
Indicate any r-th, t-th of distinguishing indexes A;mp、mq(p, q=1,2 ..., n) it is respectively any two under framework of identification Π
Two groups of basic trust partition functions that expert p, q are provided, be presented as respectively weight confidence score that expert p is provided and expert q to
Weight confidence score out is denoted as weight evidence group m respectivelypWith weight evidence group mq;mp(Ar)、mq(At) respectively indicate pth name
Expert is to subset ArTrust partition function and q experts to subset AtTrust partition function, be presented as weight evidence respectively
Group mpMiddle distinguishing indexes ArWeight confidence score, weight evidence group mqMiddle distinguishing indexes AtWeight confidence score, then evidence group
mpWith evidence group mqBetween similarity factor spqIt is represented by formula 1.
In framework of identification Π, the similarity degree between different weight evidence groups that different experts provide is different.If
The similarity of one group of weight evidence and other group of weight evidence is bigger, shows this group of weight evidence by the branch of other group of weight evidence
Hold that degree is bigger, the confidence level of this group of weight evidence is bigger.The then similarity degree between multiple groups weight evidence, is demonstrate,proved using weight
It is indicated according to group similarity factor matrix S (formula 7):
On the basis of similarity factor matrix S, every row of similarity factor matrix S is added, certain group weight evidence can be obtained
mpThe total support μ (m supported by remaining each group weight evidencep), it is indicated by formula 2.Journey is supported to each group weight evidence
Spend μ (mp) be normalized to obtain evidence mpConfidence level λ (mp), it is indicated by formula 3.If one group of weight evidence and other
Conflict between group weight evidence is larger, then the degree for showing that it is supported by other group of weight evidence is smaller, and confidence level is lower, to most
The influence of whole priority aggregation result is with regard to smaller.Distinguishing indexes weights omega (A then based on similarity factor between evidencer) can be by 4 table of formula
It reaches, which is known as decision weights, it is intended that it represents the weight status in final decision.
Based on the decision weights measuring method of above-mentioned distinguishing indexes, present invention simultaneously provides a kind of sudden basin waters
The urgent technique recognition methods of contamination accident is used for after basin happens suddenly water pollution accident, from water pollution processing technique library
The middle optimal water pollution processing technique of identification.Its technical solution is as follows:
A kind of sudden Water Basin Water Pollution accident that the decision weights measuring method using above-mentioned distinguishing indexes is realized is answered
Anxious processing technique recognition methods, for identifying most excellent water from water pollution processing technique library after basin happens suddenly water pollution accident
Pollute processing technique, it is characterised in that:
Water pollution processing technique library is made of the processing technique of different classes of water pollution, and every processing technique is marked respectively
Infuse V, V >=5 distinguishing indexes A;
Optimal water pollution processing technique identification is implemented according to following steps:
Firstly, tissue reconnaissance trip obtains field investigation data, the field investigation number after basin burst water pollution accident
According to including data suitable for each distinguishing indexes A;
Secondly, m >=3 expert scores to V distinguishing indexes A by least m, the arithmetic average of m value of every item rating is calculated
Value obtains the V item decision scoring C of every water pollution processing techniquer;
Again, by n, n >=5 expert is respectively to the weight confidence score of V distinguishing indexes A, according to the above-mentioned identification of the present invention
The decision weights measuring method of index calculates the decision weights ω (A of each distinguishing indexesr);
Finally, calculating the integrated decision-making scoring Q value of every water pollution processing technique according to formula 5:
In formula, Q-water pollution processing technique optimal identification integrated decision-making scoring,
CrAny distinguishing indexes A of-water pollution processing techniquerDecision scoring, determined by expert analysis mode,
ω(ArAny distinguishing indexes A of)-water pollution processing techniquerDecision weights, by formula 4 calculate determine,
V-distinguishing indexes A quantity;
The maximum technology of Q value is the optimal water pollution processing technique of this accident.
The urgent technique recognition methods of above-mentioned sudden Water Basin Water Pollution accident is a kind of real based on expert point rating method
Existing emergency water pollution processing technique recognition methods.This method is used for after basin happens suddenly water pollution accident, from water pollution
The optimal water pollution processing technique for being adapted to current Accident Characteristic is identified in reason technology bank.
The urgent technique recognition methods of the sudden Water Basin Water Pollution accident of the present invention needs to build water pollution processing first
Technology bank includes polymorphic type water pollution processing technique in database.Every technology is assigned the V of optimal processing technology for identification
(V >=5) item distinguishing indexes A.Environmental impact assessment specification generally can be used in distinguishing indexes A, be designed as Features of Water Environment class index,
Technology class index, economy class index, social environment class index etc..When happen suddenly water pollution accident after, tissue reconnaissance trip obtains existing
Field survey data, field investigation data are used to meet the identification needs of distinguishing indexes A.By m experts according to field investigation data
And its experience completes the value scoring of each distinguishing indexes A, obtains decision scoring Cr;Second is that by n experts according to field investigation number
According to and its experience complete the weight confidence score of each distinguishing indexes A, obtain n group weight evidence.On this basis, using the present invention
The decision weights measuring method of distinguishing indexes obtains one group of decision weights ω (A to each group weight combining evidencesr).Finally according to formula
5 calculate the integrated decision-makings scoring Q value of each part water pollution processing technique, and Q value the maximum is the optimal processing technology identified.
Optimisation technique scheme of the present invention to the urgent technique recognition methods of above-mentioned sudden Water Basin Water Pollution accident
It is:
In water pollution processing technique library, the distinguishing indexes A of every processing technique mark includes primary characterization index and second level
Distinguishing indexes.Primary characterization index totally 5, including it is suitble to water temperature range A11, be suitble to range of flow A12, be suitble to pH range A13, can
Handle pollutant concentration range A14, whether have and can rely on engineering A15(can rely on engineering is bridge or gate dam or stream or upstream lake
Library);Secondary characterization index totally 9, including applicable cases A21, removal rate A22, removal rate A23, human cost A24, goods and materials cost
A25, transportation cost A26, waste treatment cost A27, waste environment influence A28, residue environment influence A29.As
Basis, optimal water pollution processing technique identification process are divided into two stage recognition.Primary characterization is according to primary characterization index A11~A15It is complete
At determining whether the water temperature in this accident basin, flow, pH, pollutant concentration, basin have particular by field investigation can be according to
Hold in the palm the information such as engineering, then with the primary characterization index of each part technology matches in this class water pollution processing technique in database,
Thus the water pollution processing technique that can be applied to the improvement of this accident is tentatively identified.Secondary characterization is in primary characterization result
It carries out, using the present invention is based on the implementation of the technical solution of expert analysis mode, finally obtains the optimal water pollution suitable for this accident
Processing technique.5 adaptive criterias are set as primary characterization index by the prioritization scheme, can be transported by the matching of relative ease
It calculates the rejecting significant discomfort from all processing techniques and answers this accident person, then implement best techniques identification in its range of results, it can
To substantially reduce operand, the Emergency decision time is saved.
Urgent technique recognition methods around the above-mentioned sudden Water Basin Water Pollution accident of the present invention can be built relatively
The Decision System of Emergency of complete sudden Water Basin Water Pollution accident, its technical solution is as follows:
A kind of Decision System of Emergency of sudden Water Basin Water Pollution accident, including water pollution processing technique library build with it is optimal
Decision two parts;It is characterized by:
Water pollution processing technique library is built, and is to build water pollution processing technique library daily, enriches database deposit,
And whole primary characterization indexs 5 and secondary characterization index A are completed for every water pollution processing technique according to the prior art22、A23
The mark of item;
The optimizing decision, being ought after the accident, by the emergency for implementing the sudden Water Basin Water Pollution accident of the present invention
The scheme of processing technique recognition methods identifies optimal water pollution processing technique.
Above-mentioned Decision System of Emergency is dedicated to building water pollution processing technique library in the daily work, enriches database storage
It is standby, and be that every water pollution processing technique completes whole primary characterization indexs 5 and secondary characterization index A according to the prior art22、
A23The mark of item.When after the accident, implementing optimizing decision part, reconnaissance trip is organized to obtain field investigation data, group immediately
Expert's joint examination is knitted, provides field investigation data and each part processing technique secondary characterization index A to expert in time22、A23Item data,
It helps expert to complete two-level index scoring as early as possible, identifies optimal processing skill eventually by computer matching operation and expert decision-making
Art.A whole set of Decision System of Emergency can be big under the premise of reducing expert's subjectivity opinions clash, improving scoring objectivity and accuracy
The big reduction emergency response time, realize Emergency decision truly.
Compared with prior art, the beneficial effects of the present invention are: the decision weights measuring method of (1) distinguishing indexes of the present invention
Based on evidence theory thought, the weight confidence score of experts different in expert point rating method is merged and is redistributed,
To preferably by qualitative evaluation quantification, solve each expert using the weight brief combination method based on similarity factor between evidence
Conflicting between opinion, the subjectivity that can be reduced each expertise experience influence, and keep priority aggregation result more rationally effective,
Improve the Decision Quality of expert analysis mode.(2) the urgent technique recognition methods of the sudden Water Basin Water Pollution accident of the present invention
On the one hand index redundancy issue caused by can be avoided because of the potential relationship that influences each other intrinsic between distinguishing indexes reduces expert
During assessing available emergency water pollution processing technique, caused because of associated influence potential between the index being subject to
To assessment objectivity and accuracy influence;When on the other hand solving in expert analysis mode decision to distinguishing indexes scoring quantization
Conflicting problem between each fused data improves the reliability of best techniques identification.(3) the present invention provides two-stage knowledges
Other method can substantially reduce operand, save the Emergency decision time.(4) present invention a kind of sudden Water Basin Water Pollution accident
Emergency response is divided into routine work and optimizing decision two parts by the solution of Decision System of Emergency.After the accident,
Tissue need to only be puted forth effort and complete optimizing decision process, known by the primary characterization of computer matching operation and the second level of expert decision-making
Not, just it can reduce significantly emergency response under the premise of reducing expert's subjectivity opinions clash, improving scoring objectivity and accuracy
Time realizes Emergency decision truly.
Detailed description of the invention
Fig. 1 is one techniqueflow schematic diagram of embodiment.
Specific embodiment
With reference to the accompanying drawing, the preferred embodiment of the present invention is further described.
Embodiment one
As shown in Figure 1, being that certain basin burst water contamination accident identifies optimal processing technology with the method for the present invention.
1, event context and reconnaissance trip
On January 7th, 2009, the grey floodway discovery arsenic concentration of Shandong Province Linyi Pi severely exceed, and maximum concentration reaches
1.978mg/L is 39.56 times of " water environment quality standard (GB3838-2002) " III class water body standard, belongs to sudden water
Contamination accident.Investigation discovery, accident are by Shandong Hongri Acron Chemical Joint Stock Co., Ltd. in violation of rules and regulations by the tail gas of phosphoric acid production line
Circulation washing water is discharged into caused by the grey floodway of Pi.
Reconnaissance trip is organized in emergency response work immediately, obtains field investigation data.The field investigation data of acquisition include
Basin water temperature about 3 DEG C~5 DEG C, basin flow be about 180m3/ s (water volume flow rate about 2m/s), basin pH about 7.2~7.8, arsenic
Ion concentration range is the mg/L of 0.512mg/L~1.978, there are bridge and gate dam in basin, belong to possess processing technique can be according to
Hold in the palm job facilities.Accident status is one of the important component of Linyi inner city in Linyi Luozhuang District.Accident
Being related to water body is the grey floodway of Pi, belongs to middle canal water system, is one of big water system of Linyi City four, point to let out based on the flood of Yihe,
And two sides tributary is numerous.Luozhuang District, traffic convenience is the important transport hub in southern Shandong northern Suzhou, and border is worn and mistake, water transport in hundred inner Yihe
It is flourishing.Linyi City is as old revolutinary base area, and economic aspect is based on the crops such as grain, supplemented by industrial enterprise;Natural resources is few,
Large enterprise is few, and having county under its command is mostly Poor Mountainous Area, and GDP per capita ranks Shandong penultimate.
2, water pollution processing technique library describes
The water pollution processing technique database built early period has included arsenic polluted water processing technique.It is handled with arsenic polluted water
For technology, according to the data collection investigated in advance, input processing technology 13.Primary characterization is set separately in every technology
Index and secondary characterization index.The former includes being suitble to water temperature range A11, be suitble to range of flow A12, be suitble to pH range A13, can handle
Pollutant concentration range A14, whether have and can rely on engineering (such as bridge, gate dam, stream, upstream lake and reservoir) A15, amount to 5;Afterwards
Person includes applicable cases A21, removal rate A22, removal rate A23, human cost A24, goods and materials cost A25, transportation cost A26, it is discarded
Object cost of disposal A27, waste environment influence A28, residue environment influence A29, amount to 9.
According to the data collection investigated in advance, it is completed every processing technique whole primary characterization index 5 and knows with second level
Other index A22、A23The mark of item.
3, the primary characterization of processing technique
Water pollution processing technique database is run, arsenic pollution processing technique classification is chosen.According to each arsenic pollution processing technique
Applicable range/the condition of first class index, identifies 4 qualified urgent techniques, is activated alumina absorption respectively
Dam technology (t1), iron ore absorption dam technology (t2), iron chloride coagulating sedimentation technology (t3), lime precipitation technology (t4)。
4, the secondary characterization of arsenic processing technique
4.1 determine the decision scoring C of secondary characterization indexr
It has been marked by least m (m >=3, present embodiment in m=5) name expert with field investigation data and every processing technique
The A of note22、A23Based on, score according to secondary characterization index of the index standards of grading shown in table 1 to every processing technique.Meter
The arithmetic mean of instantaneous value for calculating m value of every item rating obtains 9 decisions scoring C of 5 processing techniquesr(table 2).CrIndicate every arsenic dirt
Contaminate any secondary characterization index A of processing techniquerDecision scoring.
1 secondary characterization index standards of grading of table
The decision scoring C of 2 arsenic processing technique secondary characterization index of tabler
4.2 determine the decision weights ω (A of secondary characterization indexr)
4.2.1 expert analysis mode
By n (n >=5, present embodiment in n=6), name expert is based on field investigation data, to each secondary characterization index
Weight confidence score.It is required that every expert is to the weight reliabilities of 9 indexs and is 1.Obtain n group weight evidence, every group of weight
9 weight confidence scores (table 3) of the evidence, that is, every expert to secondary characterization index.Such as any pth, 9 weights of q experts
Confidence score is referred to as p group weight evidence, q group weight evidence, is denoted as weight evidence group m respectivelyp, weight evidence group mp。
3 Weight of Expert confidence score result (part) of table
4.2.2 the decision weights ω (A of secondary characterization index is calculatedr)
According to table 3, the similarity factor s between any two groups of weight evidences is calculated according to formula 1pq.Calculating has, s12=0.9495,
s13=0.8383, s14=0.8673, s15=0.8245 ..., s1n=0.7749.
N experts are shared, then can obtain the similarity factor matrix S between each group weight evidence by formula 3:
Any weight evidence group m is calculated according to formula 2p(p=1,2 ..., n) by total support of remaining weight evidence group support
μ(mp).As a result have, μ (m1)=5.2545, μ (m2)=5.1388, μ (m3)=5.1313, μ (m4)=4.9608, μ (m5)=
4.9631,...,μ(mn)=4.7851.
Any weight evidence group m is calculated according to formula 3pConfidence level λ (mp).As a result have, λ (m1)=0.1738, λ (m2)=
0.1700, λ (m3)=0.1697, λ (m4)=0.1641, λ (m5)=0.1642 ..., λ (mn)=0.1583.
Decision weights ω (the A of secondary characterization index is calculated according to formula 4r).For example,
ω(A21)=0.1738 × 0.20+0.1700 × 0.15+0.1697 × 0.15+0.1641 × 0.4+...+0.15
83 × 0.1=0.2328.Similarly: ω (A22)=0.1933, ω (A23)=0.1322, ω (A24)=0.0493, ω (A25)=
0.0696, ω (A26)=0.0563, ω (A27)=0.0648, ω (A28)=0.0974, ω (A29)=0.1043.
Calculate the decision weights ω (A for having each secondary characterization indexr), respectively ω (A21,A22,A23, A24,A25,A26,
A27,A28,A29)=(0.2328,0.1933,0.1322,0.0493,0.0696,0.0563,0.0648,0.0974,
0.1043)。
4.3 calculate the secondary characterization integrated decision-makings scoring Q value of each arsenic processing technique
T is calculated according to formula 5 (V=9)1~t4The secondary characterization integrated decision-making scoring Q value of every processing technique.
With activated alumina absorption dam technology (t1) for calculate, Q1=0.2328 × 8.4+0.1933 × 8.6+0.1322
×8.2+0.0493×6.4+0.0696×7.0+0.0563×8 .4+0.0648×6.0+0.0974×9.2+0.1043×
9.0=8.2012 similarly: Q2=6.9762, Q3=7.7515, Q4=7.3517.That is Q (Q1,Q2,Q3,Q4)=(8.2012,
170 6.9762,7.7515, 7.3517)。
Calculated result has table 4:
The integrated decision-making appraisal result of the secondary characterization of 4 arsenic pollution processing technique of table
The display of table 4, activated alumina absorption dam technology (t1) secondary characterization comprehensive score Q value highest.Therefore, the processing skill
Art is the optimal pollution processing technique of this basin burst arsenic pollution event emergency response.The knowledge of the present embodiment optimal processing technology
Other process is about 2 days time-consuming.
In practical operation, Linyi municipal government is in starting on January 13rd, 2009 emergency preplan, domestic well-known expert's integrated environment
The monitoring results of measuring and multiple analysis experimental result of monitoring station and hydraulic department to exceeded water quality water, then through multiple meeting
Demonstration is examined, most determination in 19 days 2 months finally is using activated alumina absorption dam technology for the processing of this arsenic pollution.Entire optimal place
The recognition decision period of reason technology has a surplus up to January.
Claims (5)
1. a kind of decision weights measuring method of distinguishing indexes is closed different experts to the weight scoring of different distinguishing indexes
At obtaining the decision weights for final decision;It is characterized by: implementing according to following steps:
Firstly, determining V, V >=5 distinguishing indexes A;
Secondly, by n, n >=5 expert to the weight confidence score of V distinguishing indexes A, obtains n respectively using expert point rating method
Group weight evidence, V weight confidence score of the every group of weight evidence, that is, every expert to V distinguishing indexes A, every group of weight evidence
It is denoted as weight evidence mp, p=1,2 ..., n;
Again, the similarity factor s between any two groups of weight evidences is calculated according to formula 1pq:
In formula, spq- any two groups of weight evidences mp、mqBetween similarity factor,
mp、mq- weight evidence group mp, weight evidence group mq, it is determined by expert analysis mode,
Ar、Ar- subset Ar, subset At, indicate any r-th, t-th of distinguishing indexes A,
Ak- subset Ar, subset AtIntersection,
mp(Ar)、mq(At)-respectively indicate weight evidence group mpMiddle distinguishing indexes ArWeight confidence score, weight evidence group mqIn
Distinguishing indexes AtWeight confidence score, determined by expert analysis mode;
Again, any weight evidence group m is calculated according to formula 2p, by total support μ (m of remaining weight evidence group supportp):
In formula, μ (mp)-any weight evidence group mpThe total support supported by remaining weight evidence group;
Again, any weight evidence group m is calculated according to formula 3pConfidence level λ (mp):
In formula, λ (mp)-any weight evidence group mpConfidence level;
Finally, calculating the decision weights ω (A of distinguishing indexes according to formula 4r):
In formula, ω (Ar)-any distinguishing indexes ArDecision weights.
2. a kind of sudden Water Basin Water Pollution that the decision weights measuring method using distinguishing indexes described in claim 1 is realized
The urgent technique recognition methods of accident, for being known after basin happens suddenly water pollution accident from water pollution processing technique library
Not optimal water pollution processing technique, it is characterised in that:
Water pollution processing technique library is made of the processing technique of different classes of water pollution, and every processing technique marks V respectively,
V >=5 distinguishing indexes A;
Optimal water pollution processing technique identification is implemented according to following steps:
Firstly, tissue reconnaissance trip obtains field investigation data, the field investigation data packet after basin burst water pollution accident
It includes and meets the data that the identification of distinguishing indexes A needs;
Secondly, m >=3 expert scores to V distinguishing indexes A by least m, the arithmetic mean of instantaneous value of m value of every item rating is calculated,
Obtain the V item decision scoring C of every water pollution processing techniquer;
Again, by n, n >=5 expert to the weight confidence score of V distinguishing indexes A, refers to respectively according to identification described in claim 1
Target decision weights measuring method calculates the decision weights ω (A of each distinguishing indexesr);
Finally, calculating the integrated decision-making scoring Q value of every water pollution processing technique according to formula 5:
In formula, Q-water pollution processing technique optimal identification integrated decision-making scoring,
CrAny distinguishing indexes A of-water pollution processing techniquerDecision scoring, determined by expert analysis mode,
ω(ArAny distinguishing indexes A of)-water pollution processing techniquerDecision weights, by formula 4 calculate determine,
V-distinguishing indexes A quantity;
The maximum technology of Q value is the optimal water pollution processing technique of this accident.
3. the urgent technique recognition methods of sudden Water Basin Water Pollution accident according to claim 2, feature exist
In:
In water pollution processing technique library, the distinguishing indexes A of every processing technique mark includes primary characterization index and second level
Distinguishing indexes;The primary characterization index totally 5, including it is suitble to water temperature range A11, be suitble to range of flow A12, be suitble to pH range
A13, pollutant concentration range A can be handled14, whether have and can rely on engineering A15It is, described that rely on engineering be bridge or gate dam or river
Ditch or upstream lake and reservoir;The secondary characterization index totally 9, including applicable cases A21, removal rate A22, removal rate A23, manpower at
This A24, goods and materials cost A25, transportation cost A26, waste treatment cost A27, waste environment influence A28, residue environment
Influence A29;Database completes every processing technique whole primary characterization index 5 and secondary characterization index A22、A23The mark of item;
Optimal water pollution processing technique identification is implemented according to following steps:
Step S1, basin burst water pollution accident reconnaissance trip
Basin happens suddenly after water pollution accident, and tissue reconnaissance trip obtains field investigation data;The field investigation data include full
The data that the identification of sufficient distinguishing indexes A needs;
Step S2, the primary characterization of water pollution processing technique
Water pollution processing technique library is run, corresponding pollution processing technique classification is chosen, is applicable according to processing technique first class index
Range/condition identifies qualified water pollution processing technique, is labeled as primary characterization result technology;
Step S2, the secondary characterization of water pollution processing technique
Firstly, m >=3 expert scores to 9 secondary characterization indexs to every primary characterization result technology by least m, calculate
The arithmetic mean of instantaneous value of every item rating m value obtains 9 decisions scoring C of every primary characterization result technologyr;
Secondly, n >=5 expert to the weight confidence score of 9 secondary characterization indexs, knows respectively according to described in claim 1 by n
The decision weights measuring method of other index calculates the decision weights ω (A of each secondary characterization indexr);
The Q value finally, the integrated decision-making for calculating every primary characterization result technology is scored, the maximum technology of Q value is this accident
Optimal water pollution processing technique.
4. the urgent technique recognition methods of sudden Water Basin Water Pollution accident according to claim 3, feature exist
In:
Expert analysis mode determines the decision scoring C of secondary characterization indexrWhen, as expert according to index standards of grading shown in table 1 to every
The secondary characterization index of primary characterization result technology scores,
1 secondary characterization index standards of grading of table
The arithmetic mean of instantaneous value for calculating m value of every item rating obtains 9 decisions scoring C of every primary characterization result technologyr。
What 5. a kind of urgent technique recognition methods using sudden Water Basin Water Pollution accident as claimed in claim 4 was realized
The Decision System of Emergency of sudden Water Basin Water Pollution accident, including water pollution processing technique library are built and optimizing decision two parts;
It is characterized by:
Water pollution processing technique library is built, and is to build water pollution processing technique library daily, enriches database deposit, and root
It is that every water pollution processing technique completes whole primary characterization indexs 5 and secondary characterization index A according to the prior art22、A23?
Mark;
The optimizing decision, being ought after the accident, and the urgent technique by implementing sudden Water Basin Water Pollution accident is known
The scheme of other method identifies optimal water pollution processing technique.
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