CN110135759A - A kind of Coal Mine Security Evaluation method based on entropy weight Element Extension Model - Google Patents
A kind of Coal Mine Security Evaluation method based on entropy weight Element Extension Model Download PDFInfo
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Abstract
The invention discloses a kind of Coal Mine Security Evaluation methods based on entropy weight Element Extension Model, and the method comprising the steps of: 1) establishing evaluation index matter-element；2) evaluation index normalized；3) the Calculation Estimation index degree of association；4) Calculation Estimation index weights；5) Synthesis Relational Grade and opinion rating are determined.Present invention introduces the correlation functions in Matter element Extension to calculate the degree of association between each evaluation index and security level, the weight of each evaluation index is calculated using entropy assessment simultaneously, on this basis, find out the Synthesis Relational Grade of matter-element grade to be evaluated, according to degree of association maximum principle, safety evaluation grade is determined, finally with the reliability and reasonability of exemplary application verifying evaluation method.
Description
Technical field
The present invention relates to a kind of Coal Mine Security Evaluation methods based on entropy weight Element Extension Model, belong to Coal Mine Security Evaluation
Technical field.
Background technique
In recent years, coal mining accident plays number, severe and great casualty, ten thousand tons of death rates and declines year by year, the safety in production of China's coal-mine
Situation achieves stable progress.As the coal resources of each department are gradually exploited on a large scale, into the deep mine for adopting the stage
Gradually increase, many mines are influenced by different degrees of gas, dust, top plate etc., in deep layer high-ground stress, High-geotemperature, height
In the environment such as gas, high hydraulic pressure and high-intensitive mining exploitation, mine seems more and more frequently.In order to ensure coal mine Deep Mine
Safe working reduces safety of coal mines, reduces the incidence of accident, needs to carry out effectively Current Safety Assessment to coal mine.
Currently, being directed to Coal Mine Security Evaluation, domestic and foreign scholars are had conducted extensive research, and method mainly has: fuzzy evaluation
Method, analytic hierarchy process (AHP), probability assessment method, gray relative analysis method, fault tree analysis process, neural network etc., these theory sides
Method safe prediction, analysis and in terms of achieve preferable effect, but there is also the limitations of itself, such as traditional mould
When paste evaluation assessment, gray relative analysis method and neural network determine weight and degree of membership, there are certain subjectivities, not can guarantee
The objectivity and credibility of evaluation result；Analytic hierarchy process (AHP), fault tree analysis process are poor for the processing capacity of nonlinear organization,
And sample it is more when, calculating process is complicated；Probability assessment method requires accurately to describe the uncertainty in system, evaluation result
Accuracy and practicability be not high, has much room for improvement.There are the spies such as ambiguity, non-linear and complexity based on mine safety system itself
Sign.
Summary of the invention
The technical problem to be solved by the present invention is providing a kind of Coal Mine Security Evaluation side based on entropy weight Element Extension Model
Method, to solve above-mentioned problems of the prior art.
The technical scheme adopted by the invention is as follows: a kind of Coal Mine Security Evaluation method based on entropy weight Element Extension Model, it should
Method the following steps are included:
(1) evaluation index matter-element is established
N indicates things to be evaluated, and c indicates the title of feature, and v indicates N magnitude acquired by c.Hypothesis evaluation index etc.
Grade is divided into m grade, and safety evaluation index is n, then Classical field are as follows:
In formula: Nj(j=1,2 ..., m) indicates security level；ci(i=1,2 ..., n) indicates safety evaluation index；vjTable
Show the magnitude section of i-th of evaluation index in j grade；ajAnd bjIt indicates in security level and evaluation index magnitude section
Minimum value and maximum value；
Assuming that security level is P, then domain representation is saved are as follows:
In formula: NpFor the object to be evaluated of security level p；vpiFor ciMaximum magnitude section, apiAnd bpiIndicate safety evaluation
Minimum value and maximum value in evaluation index magnitude section corresponding to scale whole；
Assuming that matter-element to be evaluated is R, the practical achievement data being collected into is indicated are as follows:
In formula, ciIndicate index to be evaluated, viFor ciPractical index value, P0Indicate a certain specific evaluation object；
(2) evaluation index normalized
To Classical field matter-element RjAnd matter-element R to be evaluated0It is normalized, formula are as follows:
(3) the Calculation Estimation index degree of association
Point viTo finite interval vjiDistance be ρ (vi, vji), point viTo finite interval vpiDistance be ρ (vi, vpi),
In, vi, vji, vpiThe quantization index value of matter-element respectively to be evaluated, the magnitude section of Classical field and the magnitude section for saving domain, evaluation refer to
Target correlation function calculating formula are as follows:
The correlation function k of evaluation index i and grade jj(vi) is defined as:
(4) Calculation Estimation index weights
The weight of each index is calculated using entropy assessment, it is assumed that kj(vi)=rji, construct matrix are as follows:
R=(rji)m×n, (j=1,2 ..., m；I=1,2 ..., n) (7)
The entropy H of evaluation indexiIs defined as:
Wherein:(j=1,2 ..., m；I=1,2 ..., n), rjFor matrix
Element after normalized；
Evaluation criterion weight wiIs defined as:
And meet
(5) Synthesis Relational Grade and opinion rating are determined
The Synthesis Relational Grade K of matter-element p to be evaluated and grade jj(p) is defined as:
The degree of association is the correlation degree characterized between two things, and is associated with angle value closer to 1, illustrates that correlation is better,
By degree of association maximum principle, the security level K of matter-element to be evaluated is determinedj0(p), expression are as follows:
Kj0(p)=maxKi(p) (11)
Wherein:
In formula: j*For matter-element R to be evaluated0Grade variables characteristic value.Pass through j*It may determine that matter-element R to be evaluated0It deflects towards
The degree of grade.
Beneficial effects of the present invention: compared with prior art, the present invention avoids in order to objectively handle index of correlation
Subjective factor bring deviation, enhancing evaluation whole accuracy and operability, overcomes existing for different evaluation analysis method
Matter element Extension analytic approach is introduced into Coal Mine Security Evaluation by deficiency in conjunction with the characteristics of safety of coal mines index, while utilizing entropy weight
Method determines evaluation criterion weight, constructs the Coal Mine Security Evaluation model based on entropy weight Matter element Extension, and it is objective to evaluate, and evaluates accuracy
More preferably, it is introduced into the correlation function in Matter element Extension and calculates the degree of association between each evaluation index and security level, utilize simultaneously
Entropy assessment calculates the weight of each evaluation index, on this basis, the Synthesis Relational Grade of matter-element grade to be evaluated is found out, according to the degree of association
Maximum principle determines safety evaluation grade, finally with the reliability and reasonability of exemplary application verifying evaluation method.
Detailed description of the invention
Fig. 1 is sample B1~B5Rule layer weight.
Specific embodiment
With reference to the accompanying drawing and the present invention is described further in specific embodiment.
Embodiment 1: a kind of Coal Mine Security Evaluation method based on entropy weight Element Extension Model, this method include following step
It is rapid:
N indicates things to be evaluated, and c indicates the title of feature, and v indicates N magnitude acquired by c.Hypothesis evaluation index etc.
Grade is divided into m grade, and safety evaluation index is n, then Classical field are as follows:
In formula: Nj(j=1,2 ..., m) indicates security level；ci(i=1,2 ..., n) indicates safety evaluation index；vjTable
Show the magnitude section of i-th of evaluation index in j grade；aj1And bjIt indicates in security level and evaluation index magnitude section
Minimum value and maximum value；
Assuming that security level is P, then domain representation is saved are as follows:
In formula: NpFor the object to be evaluated of security level p；vpiFor ciMaximum magnitude section, apiAnd bpiIndicate safety evaluation
Minimum value and maximum value in evaluation index magnitude section corresponding to scale whole；
Assuming that matter-element to be evaluated is R, the practical achievement data being collected into is indicated are as follows:
In formula, ciIndicate index to be evaluated, viFor ciPractical index value, P0Indicate a certain specific evaluation object.
(2) evaluation index normalized
Because the level requirements of different indexs have differences, the dimension of different index feature vectors difference then needs pair
Classical field matter-element RjAnd matter-element R to be evaluated0It is normalized, formula are as follows:
(3) the Calculation Estimation index degree of association
Point viTo finite interval vjiDistance be ρ (vi, vji), point viTo finite interval vpiDistance be ρ (vi, vpi),
In, vi, vji, vpiThe quantization index value of matter-element respectively to be evaluated, the magnitude section of Classical field and the magnitude section for saving domain, evaluation refer to
Target correlation function calculating formula are as follows:
The then correlation function k of evaluation index i and grade jj(vi) is defined as:
(4) Calculation Estimation index weights
The weight of each index is calculated using entropy assessment, it is assumed that kj(vi)=rji, construct matrix are as follows:
R=(rji)m×n, (j=1,2 ..., m；I=1,2 ..., n) (7)
The entropy H of evaluation indexiIs defined as:
Wherein:(j=1,2 ..., m；I=1,2 ..., n), rjFor matrix
Element after normalized；
Evaluation criterion weight wiIs defined as:
And meet
(5) Synthesis Relational Grade and opinion rating are determined
The Synthesis Relational Grade K of matter-element p to be evaluated and grade jj(p) is defined as:
The degree of association is the correlation degree characterized between two things, and is associated with angle value closer to 1, illustrates that correlation is better,
By degree of association maximum principle, the security level K of matter-element to be evaluated is determinedj0(p), expression are as follows:
Kj0(p)=maxKi(p) (11)
Wherein:
In formula: j*For matter-element R to be evaluated0Grade variables characteristic value.Pass through j*It may determine that matter-element R to be evaluated0It deflects towards
The degree of grade.
In order to illustrate beneficial effects of the present invention, such as drag confirmatory experiment is carried out:
1, sample index and opinion rating are determined
Based on the principles such as scientific, systematicness and operability, in safety of coal mines feature and previous development preventing and controlling base
On plinth, referring to the pertinent literature of Coal Mine Security Evaluation.20 evaluations are chosen altogether and are referred to from personnel, machine, environment, management four levels
Mark establishes multi-level, multi objective Coal Mine Security Evaluation index system, is shown in Table 1.
1 Coal Mine Security Evaluation index system of table
2, Classical field, section domain and matter-element to be evaluated
According to table 1, I-V grades of Coal Mine Security Evaluation achievement data is normalized.Establish Classical field Rj
And matter-element R to be evaluated0It is shown below:
For the validity and reasonability for examining entropy weight Element Extension Model, 5 are filtered out from coal mine sample has representative
The mine B of property1、B2、B3、B4And B5As research sample and carry out contrast verification.The characteristics of according to mine safety production, by mine
Safe condition is divided into 5 grades, I grade (safety), II grade (safer), III grade (intermediate security), IV grade (more dangerous) and V
Grade (dangerous).Coal Mine Security Evaluation index division standards and sample index's measured value are specifically shown in Table 2.
The evaluation index classification standard of 2 safety of coal mines of table
3, the degree of association of evaluation index grade is determined
According to formula (5)~(6), the degree of association of each evaluation index about security level can be found out.Wherein, Kj(xi) (i=1,
2 ..., the degree of association of each opinion rating j 20) is corresponded to for i-th of index.With B1Index (C in sample1) for, correspond to 5
The degree of association of opinion rating is respectively as follows: K1(x1)=0.150, K2(x1)=- 0.150, K3(x1)=- 0.717, K4(x1)=-
0.830, K5(x1)=- 0.879, it can be determined that the index belongs to I grade of security level, i.e. " safety ".B1Sample index and safety etc.
The degree of association of grade is shown in Table 3.
3 sample B of table1The degree of association of evaluation index and security level
4, evaluation criterion weight is determined
According to formula (8)~(10), B can be found out1Each index weights of sample are as follows: (0.1177,0.0207,0.0270,
0.0422,0.0422,0.0144,0.0144,0.0144,0.2937,0.0977,0.0214,0.0165,0.0144,0.0127,
0.0315,0.0222,0.0192,0.0127,0.0421,0.1231), and then the weight of rule layer human factor, i.e. w are found out1
=0.1177+0.0207+0.0270=0.1654.Similarly find out machine factor weight w2=0.4213, environmental factor weight w3=
0.1942, management factors weight w4=0.2193.B1~B5The weight of sample rule layer, as shown in Figure 1.
By each index weights of 3 rule layer of table it is found that human factor, machine factor and environmental factor influence safety of coal mines
It is more significant.Wherein, B1The weighted value of sample machine factor is maximum, illustrates that machine factor more attaches most importance on safety of coal mines influence
It wants.Similarly, B5Sample environment factor influences the safety of coal mines even more important.By entire sample it is found that environmental factor weight
It is larger, it is more important to illustrate that it influences each safety of coal mines.Meanwhile B1Sample environment factor weight value is than machine factor and pipe
The weighted value of reason factor is low, and it is less significant to illustrate that environmental factor influences the safety of coal mines；The weighted value of management factors differs
Less, illustrate that management factors is influenced essentially identical and tended towards stability on each safety of coal mines；In contrast to machine factor and environment because
Element, management factors is to B3、B4Sample safety effects are less obvious；The weighted value of management factors and human factor is in B4、B5Sample
In it is essentially identical, both illustrate that safety of coal mines is influenced to have of equal importance.
5, sample Synthesis Relational Grade and characteristic value are determined
According to formula (11), by Matlab software, by multi-layer criteria, recursive calculation goes out destination layer B step by step1Sample and each
The degree of association after security level weighting.According to most relevance degree discrimination principle, the security level of mine is determined.Wherein, B1Sample
Security level be II grade, belong to " safer ".B can similarly be found out2~B5The degree of association after the weighting of sample security level.B1Sample
The degree of association after this weighting is shown in Table 4.
4 sample B of table1The degree of association after security level weighting
According to formula (12)~(13), B can be found out1The grade variables characteristic value j of sample*=2.489, indicate that the coal mine is pacified
Full opinion rating is biased between " safer " and " intermediate security " compared with safe condition.B can similarly be found out2~B5Sample etc.
Grade characteristics of variables value.Wherein, the data in table with underscore are most relevance degree.The security level and its wait that sample is determined entirely by
Grade characteristics of variables value is shown in Table 5.
5 sample B of table1~B5The degree of association after security level weighting
By each sample Synthesis Relational Grade of table 5 it is found that evaluation result and fuzzy mind based on entropy weight Element Extension Model totality
It is consistent through assessing network result.The evaluation result of individual samples increases compared to fuzzy neural network evaluation result.
In Element Extension Model, B1The security level of sample is II grade, is analyzed according to backward step by step, i.e., from destination layer to indicator layer by
Layer analysis.As shown in Table 3, the degree of association (0.120) of rule layer human factor is maximum, and the degree of association (- 0.383) of machine factor is most
It is small, then it can determine whether that machine factor is the key that influence sample safe condition；The indicator layer for included by machine factor is it is found that lifting
And transportation facility serviceability rate (0.400) is maximum, fire fighting device serviceability rate (- 0.933) is minimum, then emphasis is answered to reinforce fire fighting device inspection
Maintenance is repaired, to ensure the security level of coal mine.Similarly in B2 and B5 sample, the monitoring for reinforcing underground roof and floor, gas should be taken
With management measure, roof and floor supporting and the prevention and control of Gas Outburst are carried out conscientiously, reduce mine disaster accident rate；B3 sample
In this, answers emphasis to reinforce the repair and maintenance of transport, electromechanical facility, improve the usability and reliability of facility；In B4 sample, Ying Chong
Point reinforces safety education and training, promotes the safety and technical level of operating personnel, reduces the generation of unprofessional accident.In the day of mine
In normal safety inspection, step-by-step analysis is carried out for the security status of mine, and by mentioning to underground risk management and control and hidden troubles removing
Targeted Safety Measures are provided, to enhance the anti-dangerous anti-disaster ability of mine.
Conclusion: (1) the present invention is based on four personnel of safety of coal mines, machine, environment and management aspects to establish with more essence
The coal mine entropy weight Matter element Extension Model for Safety Evaluation of parasexuality and operability describes evaluation object from qualitative and quantitative 2 angles
Security level, and determine evaluation criterion weight using entropy assessment, reduce the interference of human factor, avoid index weights point
The ambiguity in subjectivity and opinion rating mixed；(2) it analyzes in conjunction with the index weights of sample and Synthesis Relational Grade it is found that ring
Border factor is more important on safety of coal mines influence, in coal mine danger source governance process, should preferentially reinforce the ring for improving underground
Border factor, while reinforcing the repair and maintenance of operating personnel's educational training and fire control facility, to more have specific aim, economy
Coal mine danger source is controlled to property, to ensure the security level of coal mine；By the Synthesis Relational Grade analysis conclusion of sample entirety it is found that can
Step-by-step analysis is carried out for the security status of mine, and by proposing that there is specific aim to underground risk management and control and hidden troubles removing
Safety Measures, to enhance the anti-dangerous anti-disaster ability of mine；(3) using entropy weight Element Extension Model to each mine sample
This safe condition carries out safety evaluation, show that the evaluation result of mine sample totality and fuzzy neural network evaluation result are kept
Unanimously, using showing that effective technological approaches can be provided for Coal Mine Security Evaluation based on entropy weight Element Extension Model.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
Those familiar with the art in the technical scope disclosed by the present invention, can easily think of the change or the replacement, and should all contain
Within protection scope of the present invention, therefore, protection scope of the present invention should be based on the protection scope of the described claims lid.
Claims (1)
1. a kind of Coal Mine Security Evaluation method based on entropy weight Element Extension Model, it is characterised in that: this method includes following step
It is rapid:
(1) evaluation index matter-element is established
N indicates things to be evaluated, and c indicates the title of feature, and v indicates N magnitude acquired by c.Hypothesis evaluation index ranking score
For m grade, safety evaluation index is n, then Classical field are as follows:
In formula: Nj(j=1,2 ..., m) indicates security level；ci(i=1,2 ..., n) indicates safety evaluation index；viIt indicates in j
The magnitude section of i-th of evaluation index in grade；aiAnd biIndicate the minimum value in security level and evaluation index magnitude section
And maximum value；
Assuming that security level is P, then domain representation is saved are as follows:
In formula: NpFor the object to be evaluated of security level p；vpiFor ciMaximum magnitude section, apiAnd bpiIndicate safety evaluation grade
Minimum value and maximum value in evaluation index magnitude section corresponding to entirety；
Assuming that matter-element to be evaluated is R, the practical achievement data being collected into is indicated are as follows:
In formula, ciIndicate index to be evaluated, viFor ciPractical index value, P0Indicate a certain specific evaluation object；
(2) evaluation index normalized
To Classical field matter-element RjAnd matter-element R to be evaluated0It is normalized, formula are as follows:
(3) the Calculation Estimation index degree of association
Point viTo finite interval vjiDistance be ρ (vi, vji), point viTo finite interval vpiDistance be ρ (vi, vpi), wherein vi,
vji, vpiThe quantization index value of matter-element respectively to be evaluated, the magnitude section of Classical field and the magnitude section for saving domain, evaluation index
Correlation function calculating formula are as follows:
The correlation function k of evaluation index i and grade jj(vi) is defined as:
(4) Calculation Estimation index weights
The weight of each index is calculated using entropy assessment, it is assumed that kj(vi)=rji, construct matrix are as follows:
R=(rji)m×n, (j=1,2 ..., m；I=1,2 ..., n) (7)
The entropy H of evaluation indexiIs defined as:
Wherein:rjIt is matrix through normalizing
Treated element；
Evaluation criterion weight wiIs defined as:
And meet
(5) Synthesis Relational Grade and opinion rating are determined
The Synthesis Relational Grade K of matter-element p to be evaluated and grade jj(p) is defined as:
By degree of association maximum principle, the security level K of matter-element to be evaluated is determinedj0(p), expression are as follows:
Kj0(p)=maxKi(p) (11)
Wherein:
In formula: j*For matter-element R to be evaluated0Grade variables characteristic value, pass through j*It may determine that matter-element R to be evaluated0Deflect towards grade
Degree.
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