CN111768057A - Evaluation method and device of DAS protection effect - Google Patents

Abstract

Embodiments of the present invention provide a DAS protection effect evaluation method and device, wherein the method includes constructing an evaluation index system including multi-level evaluation indexes; calculating the weight of each lower-level evaluation index in the evaluation index system to an upper-level evaluation index ; Divide the protection effect into several levels, and for any upper-level evaluation index, calculate the membership degree of each lower-level evaluation index of the upper-level evaluation index to the protection effect level; The weight of the upper-level evaluation index and the membership degree of each lower-level evaluation index to the protection effect level are obtained, and the fuzzy evaluation vector of the upper-level evaluation index is obtained; according to the fuzzy evaluation vector of the top-level evaluation index and the pre-construction The absolute difference of the ideal evaluation matrix is determined to determine the level of the DAS protection effect. The embodiment of the present invention realizes the comprehensive evaluation of the safety protection effect, and provides a basis for the improvement and perfection of the network safety protection scheme of the power distribution automation system.

Description

Evaluation method and device of DAS protection effect

technical field

The embodiments of the present invention relate to the technical field of power distribution networks, and more particularly, to a method for evaluating the protection effect of DAS.

Background technique

As an important part of the power network, the distribution network plays an important role in the development of the smart grid. Safety is the prerequisite for the reliable and stable operation of the distribution network, and the Distribution Automation System (DAS) is an industrial control system that ensures the safe, stable, reliable and economical operation of the distribution network. The system has functions such as distribution SCADA (supervisory control and data acquisition), fault handling, analysis and application, and interconnection with related application systems. power distribution terminals) and communication networks. With the construction and development of DAS, security incidents caused by network attacks occur frequently, which has a serious impact on the power industry.

However, for the existing DAS, there is still no objective and practical index system and method to evaluate its protective effect. Therefore, it is urgent to build an evaluation index system, carry out research on the evaluation method of DAS network security protection effect, and form a set of network security protection effect evaluation system suitable for DAS. The purpose is to provide a basis for the improvement and improvement of the protection scheme, so as to support the safe and reliable operation of the power grid.

SUMMARY OF THE INVENTION

Embodiments of the present invention provide a DAS protection effect evaluation method and device that overcomes the above problems or at least partially solves the above problems.

In a first aspect, the embodiment of the present invention provides a method for evaluating the protection effect of DAS, including:

Build an evaluation index system including multi-level evaluation indicators;

Calculate the weight of each lower-level evaluation index in the evaluation index system to the upper-level evaluation index;

Divide the protection effect into several levels, and for any upper-level evaluation index, calculate the degree of membership of each lower-level evaluation index of the upper-level evaluation index to the protection effect level;

For each upper-level evaluation index, the upper-level evaluation is obtained according to the weight of each lower-level evaluation index to the upper-level evaluation index and the degree of membership of each lower-level evaluation index to the protection effect level The fuzzy evaluation vector of the index;

Determine the level of DAS protection effect according to the fuzzy evaluation vector of the top evaluation index and the absolute difference of the pre-built ideal evaluation matrix;

The fuzzy evaluation vector is used to represent the degree of membership of the corresponding upper-level evaluation index to the protection effect level, the ideal evaluation matrix is a unit matrix, and the jth row element is used to represent the top-level evaluation index in an ideal state. The degree of membership of the protection effect of class j.

In a second aspect, an embodiment of the present invention provides a device for evaluating the protective effect of DAS, including:

The system building module is used to construct an evaluation index system including multi-level evaluation indexes;

The weight calculation module is used to calculate the weight of each lower-level evaluation index in the evaluation index system to the upper-level evaluation index;

The membership degree calculation module is used to divide the protection effect into several grades, and for any upper-level evaluation index, calculate the membership degree of each lower-level evaluation index of the upper-level evaluation index to the protection effect grade;

The fuzzy evaluation vector calculation module is used for each upper-level evaluation index, according to the weight of each lower-level evaluation index to the upper-level evaluation index and the membership degree of each lower-level evaluation index to the protection effect level , obtain the fuzzy evaluation vector of the upper-level evaluation index;

The grade determination module is used to determine the grade of the DAS protection effect according to the fuzzy evaluation vector of the top evaluation index and the absolute difference of the pre-built ideal evaluation matrix;

The fuzzy evaluation vector is used to represent the degree of membership of the corresponding upper-level evaluation index to the protection effect level, the ideal evaluation matrix is a unit matrix, and the jth row element is used to represent the top-level evaluation index in an ideal state. The degree of membership of the protection effect of class j

In a third aspect, an embodiment of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor, the processor implementing the program as described in the first aspect when the processor executes the program Steps of the provided method.

In a fourth aspect, an embodiment of the present invention provides a non-transitory computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, implements the steps of the method provided in the first aspect.

The DAS protection effect evaluation method and device provided by the embodiments of the present invention comprehensively consider the main power distribution station, distribution terminal, communication network, boundary and other levels, and can comprehensively measure the protection effect, and the analytic hierarchy process is used to calculate the index weight, The results of qualitative analysis can be quantified and easily realized. Based on the constructed evaluation index system, an improved fuzzy comprehensive evaluation method is used to calculate the correlation between the evaluation object and the ideal evaluation vector. The calculation result can objectively and accurately reflect the protection effect level and realize the comprehensive evaluation of the safety protection effect. It provides a basis for the improvement and perfection of the network security protection scheme of the distribution automation system.

Description of drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description These are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained according to these drawings without creative efforts.

1 is a schematic flowchart of a method for evaluating a DAS protection effect provided in an embodiment of the present invention;

2 is a schematic diagram of a network security protection effect evaluation index system of a power distribution automation system provided by an embodiment of the present invention;

3 is a schematic structural diagram of an evaluation device for DAS protection effect provided by an embodiment of the present invention;

FIG. 4 is a schematic diagram of a physical structure of an electronic device according to an embodiment of the present invention.

Detailed ways

In order to make the purposes, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments These are some embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

FIG. 1 is a schematic flowchart of a method for evaluating the protection effect of DAS provided by an embodiment of the present invention. As shown in FIG. 1 , the evaluation method includes steps S101, S102, S103, S104, and S105. Specifically,

S101 , constructing an evaluation index system including multi-level evaluation indexes.

Specifically, according to the DAS business process and system architecture characteristics, the embodiment of the present invention conducts network security risk analysis from four levels of power distribution terminal, communication channel, power distribution main station and boundary, and reasonably selects and evaluates in combination with the adopted security protection scheme index, and build an evaluation index system.

FIG. 2 is a schematic diagram of an evaluation index system for the network security protection effect of a power distribution automation system provided by an embodiment of the present invention. As shown in FIG. 2 , the target layer of the evaluation index system is the DAS network security protection effect, which belongs to the top evaluation index; The evaluation index (referred to as the first-level index) is the safety protection effect of the main power distribution station, power distribution terminal, communication network, and boundary.

For the main power distribution station, the embodiment of the present invention proposes to select identity authentication, data security, host security protection and access control, a total of 4 secondary evaluation indicators (referred to as secondary evaluation indicators).

For power distribution terminals, the embodiment of the present invention proposes to select identity authentication, physical security protection, self-security protection, interaction with on-site operation and maintenance tools, data security, malicious code prevention and intrusion prevention, a total of 7 secondary indicators.

For the communication network, the embodiment of the present invention proposes to select access authentication, communication mode, network isolation, access control, data security, equipment protection and network attack protection, a total of 7 secondary indicators.

For the boundary, the embodiment of the present invention proposes to select five secondary indicators in total, including intrusion prevention, malicious code prevention, access control, auditing, and boundary isolation.

S102: Calculate the weight of each lower-level evaluation index in the evaluation index system to the upper-level evaluation index.

Specifically, in this embodiment of the present invention, experts in the field of DAS security protection can determine the weight based on experience. Of course, in order to accurately determine the weight of the next-level evaluation index to the previous-level evaluation index from an objective point of view, the embodiment of the present invention can use operational research Theories are used for analysis, such as AHP, fuzzy method, fuzzy AHP, expert evaluation method and so on. As a preferred embodiment, the embodiment of the present invention adopts the Analytic Hierarchy Process (AHP) for analysis. AHP refers to decomposing elements that are always related to decision-making into levels such as goals, criteria, and plans. Qualitative and quantitative analysis of decision-making methods. It should be noted that the weight of the next-level evaluation index to the previous-level evaluation index is the degree of importance of the next-level evaluation index to the previous-level evaluation index. The sum of the weights of the next-level evaluation indicators is 1.

S103. Divide the protection effect into several levels, and for any one upper-level evaluation index, calculate the degree of membership of each lower-level evaluation index of the upper-level evaluation index to the protection effect level.

Specifically, on the basis of the above steps, the embodiment of the present invention adopts the fuzzy comprehensive evaluation method to calculate the degree of membership of each lower-level evaluation index of the upper-level evaluation index to the protection effect level. This comprehensive evaluation method transforms qualitative evaluation into quantitative evaluation according to the membership degree theory of fuzzy mathematics, that is, using fuzzy mathematics to make a general evaluation of things or objects restricted by many factors. It has the characteristics of clear results and strong systematicness, can better solve vague and difficult to quantify problems, and is suitable for solving various non-deterministic problems.

The discrimination and quantification of the membership degree in the embodiment of the present invention can be determined by an expert based on the actual situation of the implementation of the DAS security protection measures by using a linear membership degree function. It can be understood that, for a next-level evaluation index, the sum of the membership degrees of the next-level evaluation index to all protection effect levels is 1.

S104. For each upper-level evaluation index, obtain the upper-level evaluation index according to the weight of each lower-level evaluation index to the upper-level evaluation index and the membership degree of each lower-level evaluation index to the protection effect level Fuzzy evaluation vector of grade evaluation index.

Specifically, if an upper-level evaluation index A has three lower-level evaluation indexes a, b and c, the protection effect level is divided into three levels: A, B, and C; if the weights of a, b, and c to A are respectively are 0.2, 0.3 and 0.5, while the membership degree of a to the protection effect level is 1, 0, 0, the membership degree of b to the protection effect level is 0, 1, 0, and the membership degree of c to the protection effect level is 1, 0 , 0, then the fuzzy evaluation vector of A can be calculated by the following formula:

Obviously, the fuzzy evaluation vector is used to represent the degree of membership of the previous evaluation index to the protection effect level. From the above results, it can be seen that the evaluation index A has a degree of membership of 0.7 for the protection effect of grade A, and a degree of membership of 0.3 for the protection effect of grade B. degree, and 0 membership degree for the C-level protection effect. Obviously, through step S104, the fuzzy evaluation vectors of all evaluation indexes can be derived layer by layer, that is, the degree of membership to the protection effect level.

S105: Determine the level of the DAS protection effect according to the fuzzy evaluation vector of the top evaluation index and the absolute difference of the ideal evaluation matrix constructed in advance. The ideal evaluation matrix is a unit matrix, and the elements in the m-th row are used to represent the membership degree of the top-level evaluation index to the m-th level protection effect in an ideal state.

若评价向量P的第z个分量最大时，可认为评价指标近似属于等级V_Z，因此给出理想评价向量P_z＝(…,1,…)，其中第z个分量为1。理想评价矩阵就是由m行理想评价向量组成。When given an evaluation vector P=(p ₁ ,p ₂ ,...,p _n ), where p _j is the membership degree of the evaluation index belonging to level j and

If the z-th component of the evaluation vector P is the largest, it can be considered that the evaluation index approximately belongs to the level V _Z , so an ideal evaluation vector P _z =(...,1,...) is given, where the z-th component is 1. The ideal evaluation matrix is composed of m rows of ideal evaluation vectors.

In the embodiment of the present invention, the evaluation results are divided into five levels, so the ideal evaluation vectors set are P ₁ =(1,0,0,0,0), P ₂ =(0,1,0,0,0) , P ₃ =(0,0,1,0,0), P ₄ =(0,0,0,1,0), P ₅ =(0,0,0,0,1), constitute an ideal evaluation matrix , as shown in Table 3:

Table 3 The ideal evaluation matrix table of the embodiment of the present invention

For the element in the mth row of the ideal evaluation matrix, calculate the absolute difference _Δmj between each element in the mth row and the corresponding element in the fuzzy evaluation vector B, where j represents the jth column element in the ideal evaluation matrix and the fuzzy evaluation vector;

Calculate the correlation coefficient θ _mj between the fuzzy evaluation vector B and each element of the mth row according to the following formula:

Among them, _Δmax represents the maximum absolute difference between all elements in the ideal evaluation matrix and the corresponding element in the fuzzy evaluation vector B, _Δmin represents the minimum absolute difference between all elements in the ideal evaluation matrix and the corresponding element in the fuzzy evaluation vector B, and α is 0.5;

确定模糊评价向量B与理想评价矩阵第m行元素的关联度σ_BVm；可以理解的是，；理想评价矩阵的第m行元素用于表征第m个评价效果等级，计算模糊评价向量B与理想评价矩阵第m行元素的关联度，意味着计算顶层评价指标与第m个评价效果的关联度。According to the formula

Determine the degree of correlation σ _BVm between the fuzzy evaluation vector B and the element in the mth row of the ideal evaluation matrix; it can be understood that the element in the mth row of the ideal evaluation matrix is used to characterize the mth evaluation effect level, and calculate the fuzzy evaluation vector B and the ideal The correlation degree of the elements in the mth row of the evaluation matrix means calculating the correlation degree between the top-level evaluation index and the mth evaluation effect.

The correlation degree between the fuzzy evaluation vector B and all protection effect levels is calculated, and the protection effect level corresponding to the maximum correlation degree is taken as the level of the DAS protection effect.

It should be noted that the embodiment of the present invention comprehensively considers the main power distribution station, power distribution terminal, communication network, boundary and other levels, can comprehensively measure the protection effect, and uses the analytic hierarchy process to calculate the index weight, which can be used to analyze the results of qualitative analysis. Quantitative and easy to implement. Based on the constructed evaluation index system, an improved fuzzy comprehensive evaluation method is used to calculate the correlation between the evaluation object and the ideal evaluation vector. The calculation result can objectively and accurately reflect the protection effect level and realize the comprehensive evaluation of the safety protection effect. It provides a basis for the improvement and perfection of the network security protection scheme of the distribution automation system.

On the basis of the above embodiments, as an optional embodiment, the weight of each lower-level evaluation index in the evaluation index system to the upper-level evaluation index is calculated, specifically:

A plurality of judgment matrices are constructed according to the stages of the evaluation index system, and the judgment matrices are used to represent the importance degree between two lower-level evaluation indexes among all the lower-level evaluation indexes for the same upper-level evaluation index ratio;

Carry out consistency check on the judgment matrix, if the consistency check is satisfied, then normalize the eigenvector corresponding to the maximum eigenvalue of the judgment matrix to obtain each next-level evaluation in the judgment matrix The weight of the index to the upper-level evaluation index.

Specifically, in the embodiment of the present invention, the importance levels of the next-level evaluation indicators are compared pair-wise, and a judgment matrix A=[a _ij ] _n×n , where a _ij represents the ratio of the importance of the next-level evaluation indicators i and j to the evaluation object, and n represents the number of the next-level evaluation indicators.

Table 1 Proportional scale table of the importance of evaluation indicators

For example, if a ₂₁ is 5, it means that the evaluation index 2 is more important than the evaluation index 1 to the upper-level evaluation index; if a ₂₃ is 4, it means that the evaluation index 2 is more important than the evaluation index 3 to the upper-level evaluation index. The effect is between clearly important and strongly important, and accordingly, a ₁₂ is defined as 1/5, the reciprocal of 5, and a ₃₂ is defined as 1/4.

On the basis of the above embodiments, as an optional embodiment, the consistency check is performed on the judgment matrix, specifically:

The consistency indicator CI is calculated according to the following formula:

Among them, n is the number of the next-level evaluation index of the previous-level evaluation index corresponding to the judgment matrix, and λ _max represents the maximum eigenvalue of the judgment matrix.

If CI=0, the judgment matrix is completely consistent, otherwise, the random consistency ratio CR is calculated:

Among them, RI is the average random consistency index (the value is shown in Table 2, and n in the table is the number of the next-level evaluation index corresponding to the upper-level evaluation index corresponding to the judgment matrix).

Table 2 Average random consistency index RI

When CR≤0.10, the judgment matrix satisfies the consistency, otherwise it is necessary to adjust the value of the elements in the judgment matrix and re-consistency judgment until the consistency is satisfied.

Calculate the maximum eigenvalue of the judgment matrix that satisfies the consistency check and the eigenvector corresponding to the maximum eigenvalue, and normalize the eigenvector to obtain the required weight. According to the definition of eigenvalues, the number of elements of eigenvalues is consistent with the number of next-level evaluation indicators.

Since the object to be evaluated in the embodiment of the present invention involves multiple factors and multiple levels, the embodiment of the present invention proposes an improved fuzzy comprehensive evaluation method, and the main steps of the method are as follows:

(1) Determine the factor set and weight vector

The factor set U and weight W are determined according to the evaluation index system. Taking the network security protection effect evaluation index system of the distribution automation system shown in Figure 2 as an example, the first-level index factor set is U={U ₁ , U ₂ ,...U _i ,...U _l }, the factor set of the secondary index is U _i ={U _i1 ,U _i2 ,...U _iT }, the weight vector of the primary evaluation index is: W={w ₁ ,w ₂ ,...w _l }, the weight vector of secondary indicators is W _i ={ _wi1 , _wi2 ,...w _iT }, where l represents the number of primary indicator factors, and T represents the number of secondary indicator factors corresponding to the primary indicator factor number,

(2) Determine the evaluation set

The protection effect is divided into five grades: good, good, general, poor, and poor (good, good, general, poor, and poor are 1, 2, 3, 4, and 5 in turn), and the evaluation set is determined as V = {V ₁ , V ₂ , V ₃ , V ₄ , V ₅ }, quantified as fractions {X ₁ , X ₂ , X ₃ , X ₄ , X ₅ } = {100, 80, 60, 40, 20}, The level difference θ is 20.

(3) Calculate the membership degree and construct the judgment matrix

其中r_ij表示第i个下一级评价指标对第j个评价等级的隶属度，T表示上一级评价指标i具有的下一级评价指标的个数，J表示防护效果等级的个数。Construct the evaluation matrix R _i of l first-level indicators, such as

where r _ij represents the degree of membership of the i-th next-level evaluation index to the j-th evaluation level, T represents the number of next-level evaluation indexes possessed by the previous-level evaluation index i, and J represents the number of protection effect levels.

The discrimination and quantification of membership degree can be determined by experts based on the actual situation of DAS security protection measures, giving the score x and using a linear membership function to determine.

The next-level evaluation index x belongs to the membership degree of the first protection effect level:

The next-level evaluation index x belongs to the membership degree of the j-th protection effect level (1<j<J):

The next-level evaluation index x belongs to the membership degree of the J-th protection effect level:

Among them, X _j represents the score of the j-th protection effect level; θ represents the difference between the scores of two adjacent protection effect levels.

(4) Determine the fuzzy evaluation vector and the ideal evaluation matrix

Calculate the fuzzy evaluation vector of the first-level index:

B _i =W _i ·R _i

计算目标层(即顶层)的模糊评价向量B＝(b₀₁,b₀₂,…,b_0j,…,b_0J)：b_0j表示顶级的评价指标属于第j级防护效果的隶属度：The target layer evaluation matrix is composed of B _i

Calculate the fuzzy evaluation vector B=(b ₀₁ ,b ₀₂ ,…,b _0j ,…,b _0J ) of the target layer (that is, the top layer): b _0j indicates that the top evaluation index belongs to the membership degree of the j-th protection effect:

B=W·R

(5) Calculate the correlation coefficient

Calculate the absolute difference _Δmj between the ideal evaluation matrix and the fuzzy evaluation vector B, where m represents the mth row element;

Δ _mj =|p _mj -b _0j |

Find the maximum difference Δ _max and the minimum difference Δ _min among them, and calculate the correlation coefficient θ _mj :

Among them, α can take 0.5.

(6) Determine the evaluation level

Find the correlation degree σ _BVm between the fuzzy evaluation phasor and the ideal evaluation vector:

Find out the maximum degree of correlation, so as to determine the evaluation level V _m of the network security protection effect of the distribution automation system.

FIG. 3 is a schematic structural diagram of an evaluation device for DAS protection effect provided by an embodiment of the present invention. As shown in FIG. 3 , the evaluation device for DAS protection effect includes: a system construction module 301, a weight calculation module 302, a membership degree calculation module 303, Fuzzy evaluation vector calculation module 304 and level determination module 305, wherein:

The system construction module 301 is used to construct an evaluation index system including multi-level evaluation indexes;

The weight calculation module 302 is used to calculate the weight of each lower-level evaluation index in the evaluation index system to the upper-level evaluation index;

The membership degree calculation module 303 is used to divide the protection effect into several levels, and for any one upper-level evaluation index, calculate the degree of membership of each lower-level evaluation index of the upper-level evaluation index to the protection effect level;

The fuzzy evaluation vector calculation module 304 is used for each upper-level evaluation index, according to the weight of each lower-level evaluation index to the upper-level evaluation index and the affiliation of each lower-level evaluation index to the protection effect level degree, obtain the fuzzy evaluation vector of the upper-level evaluation index;

The grade determination module 305 is used to determine the grade of the DAS protection effect according to the fuzzy evaluation vector of the top evaluation index and the absolute difference of the ideal evaluation matrix constructed in advance;

The fuzzy evaluation vector is used to represent the degree of membership of the corresponding upper-level evaluation index to the protection effect level, the ideal evaluation matrix is a unit matrix, and the jth row element is used to represent the top-level evaluation index in an ideal state. The degree of membership of the protection effect of class j.

The device for evaluating the DAS protection effect provided by the embodiment of the present invention specifically implements the process of the above-mentioned embodiments of the evaluation methods for the DAS protection effects. The device for evaluating the protection effect of DAS provided by the embodiment of the present invention comprehensively considers the main power distribution station, power distribution terminal, communication network, boundary and other levels, and can comprehensively measure the protection effect. The results of the analysis are quantified and easy to implement. Based on the constructed evaluation index system, an improved fuzzy comprehensive evaluation method is used to calculate the correlation between the evaluation object and the ideal evaluation vector. The calculation result can objectively and accurately reflect the protection effect level and realize the comprehensive evaluation of the safety protection effect. It provides a basis for the improvement and perfection of the network security protection scheme of the distribution automation system.

FIG. 4 is a schematic diagram of an entity structure of an electronic device provided by an embodiment of the present invention. As shown in FIG. 4 , the electronic device may include: a processor (processor) 410, a communications interface (Communications Interface) 420, a memory (memory) 430, and a communication The bus 440, wherein the processor 410, the communication interface 420, and the memory 430 complete the communication with each other through the communication bus 440. The processor 410 may call a computer program stored in the memory 430 and run on the processor 410 to execute the DAS protection effect evaluation method provided by the above embodiments, for example, including: constructing an evaluation index system including multi-level evaluation indicators. ; Calculate the weight of each lower-level evaluation index in the evaluation index system to the upper-level evaluation index; divide the protection effect into several levels, and for any upper-level evaluation index, calculate the weight of each upper-level evaluation index. The degree of membership of each lower-level evaluation index to the protection effect level; for each upper-level evaluation index, according to the weight of each lower-level evaluation index to the upper-level evaluation index and the pair of each lower-level evaluation index The membership degree of the protection effect grade is obtained, and the fuzzy evaluation vector of the upper-level evaluation index is obtained; according to the fuzzy evaluation vector of the top evaluation index and the absolute difference of the pre-built ideal evaluation matrix, the grade of the DAS protection effect is determined; The fuzzy evaluation vector is used to represent the degree of membership of the corresponding upper-level evaluation index to the protection effect level, the ideal evaluation matrix is a unit matrix, and the jth row element is used to represent the top evaluation index in the ideal state to the jth level protection. Membership of the effect.

In addition, the above-mentioned logic instructions in the memory 430 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solutions of the embodiments of the present invention are essentially, or the parts that make contributions to the prior art or the parts of the technical solutions can be embodied in the form of software products, and the computer software products are stored in a storage medium , including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes: U disk, removable hard disk, Read-Only Memory (ROM, Read-Only Memory), Random Access Memory (RAM, Random Access Memory), magnetic disk or optical disk and other media that can store program codes .

Embodiments of the present invention also provide a non-transitory computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, is implemented to perform the DAS protection effect evaluation method provided by the foregoing embodiments, for example, including : Build an evaluation index system including multi-level evaluation indicators; calculate the weight of each lower-level evaluation index in the evaluation index system to the upper-level evaluation index; divide the protection effect into several levels, and evaluate any upper-level evaluation index. , calculate the degree of membership of each lower-level evaluation index of the upper-level evaluation index to the protection effect level; for each upper-level evaluation index, according to each lower-level evaluation index to the upper-level evaluation index and the membership degree of each lower-level evaluation index to the protection effect level, obtain the fuzzy evaluation vector of the upper-level evaluation index; according to the fuzzy evaluation vector of the top-level evaluation index and the absolute difference of the pre-built ideal evaluation matrix , determine the level of DAS protection effect; wherein, the fuzzy evaluation vector is used to represent the degree of membership of the corresponding upper-level evaluation index to the protection effect level, the ideal evaluation matrix is a unit matrix, and the jth row element is used to represent the ideal The membership degree of the top evaluation index in the state to the j-th protection effect.

The device embodiments described above are only illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in One place, or it can be distributed over multiple network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution in this embodiment. Those of ordinary skill in the art can understand and implement it without creative effort.

From the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and certainly can also be implemented by hardware. Based on this understanding, the above-mentioned technical solutions can be embodied in the form of software products in essence or the parts that make contributions to the prior art, and the computer software products can be stored in computer-readable storage media, such as ROM/RAM, magnetic A disc, an optical disc, etc., includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform the methods described in various embodiments or some parts of the embodiments.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, but not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand: it can still be Modifications are made to the technical solutions described in the foregoing embodiments, or some technical features thereof are equivalently replaced; and these modifications or replacements do not make the essence of the corresponding technical solutions depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (10)

1. an evaluation method of DAS protective effect, is characterized in that, comprises: Build an evaluation index system including multi-level evaluation indicators; Calculate the weight of each lower-level evaluation index in the evaluation index system to the upper-level evaluation index; Divide the protection effect into several levels, and for any upper-level evaluation index, calculate the degree of membership of each lower-level evaluation index of the upper-level evaluation index to the protection effect level; For each upper-level evaluation index, the upper-level evaluation is obtained according to the weight of each lower-level evaluation index to the upper-level evaluation index and the degree of membership of each lower-level evaluation index to the protection effect level The fuzzy evaluation vector of the index; Determine the level of DAS protection effect according to the fuzzy evaluation vector of the top evaluation index and the absolute difference of the pre-built ideal evaluation matrix; The fuzzy evaluation vector is used to represent the degree of membership of the corresponding upper-level evaluation index to the protection effect level, the ideal evaluation matrix is a unit matrix, and the jth row element is used to represent the top-level evaluation index in an ideal state. The degree of membership of the protection effect of class j. 2. evaluation method according to claim 1 is characterized in that, the weight of each next-level evaluation index to upper-level evaluation index in the described calculation evaluation index system, is specifically: A plurality of judgment matrices are constructed according to the stages of the evaluation index system, and the judgment matrices are used to represent the importance degree between two lower-level evaluation indexes among all the lower-level evaluation indexes for the same upper-level evaluation index ratio; Carry out consistency check on the judgment matrix, if the consistency check is satisfied, then normalize the eigenvector corresponding to the maximum eigenvalue of the judgment matrix to obtain each next-level evaluation in the judgment matrix The weight of the index to the upper-level evaluation index. 3. The evaluation method according to claim 2, wherein the said judgment matrix is checked for consistency, specifically: The consistency indicator CI is calculated according to the following formula:

Among them, n is the number of the next-level evaluation index of the upper-level evaluation index corresponding to the judgment matrix, and λ _max represents the maximum eigenvalue of the judgment matrix; If CI is equal to 0, it is determined that the judgment matrix passes the consistency check; If CI is not equal to 0, the consistency ratio CR is calculated according to the following formula:

Wherein, RI is a predetermined average random consistency index; if CR≤0.1, it is determined that the judgment matrix passes the consistency check. 4. The evaluation method according to claim 1, wherein, for any one upper-level evaluation index, the degree of membership of each lower-level evaluation index of the upper-level evaluation index to the protection effect level is calculated ,Specifically: The next-level evaluation index x belongs to the membership degree of the first protection effect level:

The next-level evaluation index x belongs to the membership degree of the j-th protection effect level (1<j<J):

The next-level evaluation index x belongs to the membership degree of the J-th protection effect level:

Among them, X _j represents the score of the j-th protection effect level; θ represents the difference between the scores of two adjacent protection effect levels. 5 . The evaluation method according to claim 1 , wherein the weight of the upper-level evaluation index according to each lower-level evaluation index and the affiliation of each lower-level evaluation index to the protection effect level. 6 . degree to obtain the fuzzy evaluation vector of the upper-level evaluation index, specifically: For any upper-level evaluation index i, construct the evaluation matrix

and weight vector W _i ={w ₁ ,w ₂ ,...w _T }; wherein, T represents the number of next-level evaluation indexes possessed by the previous-level evaluation index i, and J represents the number of protection effect levels; The fuzzy evaluation vector B _i of the upper-level evaluation index i is calculated according to the formula B _i =W _i ·R _i . 6. The evaluation method according to claim 1, wherein the fuzzy evaluation vector defining the top evaluation index is B=(b ₀₁ ,b ₀₂ ,...,b _0j ,...,b _0J ), and b _0j represents the top level The evaluation index belongs to the membership degree of the j-th protection effect; Correspondingly, the level of the DAS protection effect is determined according to the fuzzy evaluation vector of the top evaluation index and the absolute difference of the ideal evaluation matrix constructed in advance, specifically: For the element in the mth row of the ideal evaluation matrix, calculate the absolute difference _Δmj between each element in the mth row and the corresponding element in the fuzzy evaluation vector B, where j represents the jth column element in the ideal evaluation matrix and the fuzzy evaluation vector; The correlation coefficient θ _mj between the fuzzy evaluation vector B and the element in the mth row is calculated according to the following formula:

Among them, _Δmax represents the maximum absolute difference between all elements in the ideal evaluation matrix and the corresponding element in the fuzzy evaluation vector B, _Δmin represents the minimum absolute difference between all elements in the ideal evaluation matrix and the corresponding element in the fuzzy evaluation vector B, and α is 0.5; According to the formula

Determine the degree of correlation σ _{BVm between} the fuzzy evaluation vector B and the element in the mth row of the ideal evaluation matrix; The correlation degree between the fuzzy evaluation vector B and all protection effect levels is calculated, and the protection effect level corresponding to the maximum correlation degree is taken as the level of the DAS protection effect. 7 . The evaluation method according to claim 3 , wherein if CR>0.1, the judgment matrix is adjusted until the consistency check is passed. 8 . 8. A device for evaluating the protective effect of DAS, characterized in that, comprising: The system building module is used to construct an evaluation index system including multi-level evaluation indexes; The weight calculation module is used to calculate the weight of each lower-level evaluation index in the evaluation index system to the upper-level evaluation index; The membership degree calculation module is used to divide the protection effect into several grades, and for any upper-level evaluation index, calculate the membership degree of each lower-level evaluation index of the upper-level evaluation index to the protection effect grade; The fuzzy evaluation vector calculation module is used for each upper-level evaluation index, according to the weight of each lower-level evaluation index to the upper-level evaluation index and the membership degree of each lower-level evaluation index to the protection effect level , obtain the fuzzy evaluation vector of the upper-level evaluation index; The grade determination module is used to determine the grade of the DAS protection effect according to the fuzzy evaluation vector of the top evaluation index and the absolute difference of the pre-built ideal evaluation matrix; The fuzzy evaluation vector is used to represent the degree of membership of the corresponding upper-level evaluation index to the protection effect level, the ideal evaluation matrix is a unit matrix, and the jth row element is used to represent the top-level evaluation index in an ideal state. The degree of membership of the j-level protective effect. 9. An electronic device, characterized in that, comprising: at least one processor; and at least one memory communicatively coupled to the processor, wherein: The memory stores program instructions executable by the processor, and the processor invokes the program instructions to execute the DAS protection effect evaluation method according to any one of claims 1 to 7. 10. A non-transitory computer-readable storage medium, characterized in that the non-transitory computer-readable storage medium stores computer instructions, the computer instructions cause the computer to execute any one of claims 1 to 7 The evaluation method of the described DAS protection effect.

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