Scenic spot lightning disaster risk evaluation method based on game empowerment and regret theory

Abstract

The invention provides a scenic spot lightning disaster risk evaluation method based on game empowerment and a regret theory. The method comprises the following steps: S1, obtaining scenic spot lightning disaster risk evaluation index parameters; s2, improving an analytic hierarchy process to determine a subjective weight in scenic spot lightning disaster risk evaluation; s3, determining an objective weight in scenic spot lightning disaster risk evaluation by an entropy weight method; s4, combining the subjective weight and the objective weight obtained in the steps S2 and S3, and utilizing a game weighting method to determine a comprehensive weight in scenic spot thunder and lightning disaster risk evaluation; s5, performing coupling evaluation on the comprehensive weight in the step S4 and a regret theory; and S6, finally obtaining a thunder and lightning disaster risk evaluation value and grade. The comprehensive weight of scenic spot lightning disaster risk evaluation is determined by adopting a game empowerment method, the advantage of risk avoidance of an evaluation result is fully played by utilizing a regret theory evaluation method, and the main cause influencing the lightning disaster risk is found out according to the to-be-improved component of each index.

Description

Technical Field

[0001] The present invention relates to the technical field, and specifically to a scenic area lightning disaster risk assessment method based on game weighting and regret theory. Background Art

[0002] To improve the rationality and effectiveness of scenic area lightning disaster risk assessment, based on the analysis of the advantages and disadvantages of various assessment methods, a scenic area lightning disaster risk assessment scheme based on game weighting and regret theory is proposed. The subjective weight is obtained by using the improved analytic hierarchy process, the objective weight is calculated by using the entropy weight method, and the comprehensive weight of the evaluation index is determined by the game weighting method, overcoming the deficiencies of determining weights by the subjective and objective methods. Utilizing the risk aversion characteristics of regret theory, the comprehensive weight is coupled with regret theory to establish a game weighting-regret theory evaluation model. The evaluation is carried out according to the scenic area lightning disaster risk assessment index parameter system and the risk level determination standard, and the evaluation results are obtained and compared with other methods to verify the accuracy and reliability of the game weighting-regret theory evaluation model. Through further analysis, the main reasons affecting the scenic area lightning disaster risk are found out, and specific measures to reduce the risk are proposed, providing new ideas and methods for lightning disaster risk assessment and lightning protection and disaster reduction work. Summary of the Invention

[0003] (1) Technical Problems to be Solved

[0004] Aiming at the deficiencies of the prior art, the present invention provides a scenic area lightning disaster risk assessment method based on game weighting and regret theory, which improves the accuracy and reliability of the scenic area lightning disaster risk assessment results and solves the problem of difficult to find out the main reasons affecting the scenic area lightning disaster risk.

[0005] (2) Technical Solutions

[0006] To achieve the above object, the present invention is realized through the following technical solutions: A scenic area lightning disaster risk assessment method based on game weighting and regret theory, comprising the following steps:

[0007] S1. Obtaining the scenic area lightning disaster risk assessment index parameters;

[0008] S2. Determining the subjective weight in the scenic area lightning disaster risk assessment by using the improved analytic hierarchy process;

[0009] S3. Determining the objective weight in the scenic area lightning disaster risk assessment by using the entropy weight method;

[0010] S4. Then, combining the subjective weight and the objective weight obtained in the above steps S2 and S3, using the game weighting method to determine the comprehensive weight in the scenic area lightning disaster risk assessment;

[0011] S5. Further coupling and evaluating the comprehensive weight in step S4 with regret theory;

[0012] S6. Finally, obtain the lightning disaster risk evaluation value and level.

[0013] Preferably, in step S1, there are many factors affecting the lightning disaster risk in the scenic area, and there is a certain correlation between them. According to the risk characteristics of different types of scenic areas and in accordance with the classical risk management theory, collect lightning disaster risk evaluation index parameters from four aspects: hazard-causing factors, disaster-bearing environments, disaster-affecting characteristics, and disaster prevention capabilities.

[0014] Preferably, the hazard-causing factor of the lightning disaster in the scenic area is the lightning activity itself. The density of lightning strikes on the ground, the intensity of lightning current, and the lightning disasters that have occurred in the scenic area and its surrounding areas in history are all important indicators representing the intensity of lightning activity.

[0015] Preferably, the disaster-bearing environment is actually the environmental characteristics of the area where the scenic area is located. The level of soil resistivity, the characteristics of the terrain and landform, and the surrounding environmental conditions are all potential factors affecting the occurrence of lightning disasters.

[0016] Preferably, the disaster-affecting characteristics are the characteristic parameters related to lightning disasters in the scenic area itself, mainly including the number of tourists and the visiting duration related to personnel activities, as well as the area, structure, and height related to the characteristics of buildings, and the situation of electronic and electrical systems related to equipment.

[0017] Preferably, the disaster prevention capabilities mainly include the technical measures, management measures, and emergency measures taken by the scenic area in lightning protection and disaster reduction, specifically divided into indicators such as the setting, detection, and early warning measures of lightning protection devices, as well as management systems, science popularization publicity, emergency plans, evacuation drills, etc.

[0018] Preferably, the improved analytic hierarchy process uses 3 scales to judge the relative importance between two indicators, significantly reducing the influence of decision-makers' subjective factors, not requiring consistency testing, with a simple process, fast calculation, and being able to meet the accuracy requirements. Step S2 includes the following steps:

[0019] S2A. Construct a comparison matrix: A = (a ij ) n×n ;

[0020] S2B. Calculate the optimal transfer matrix: R = (r ij ) n×n ;

[0021] S2C. Calculate the judgment matrix: D = (d ij ) n×n ;

[0022] S2D. Calculate the weight vector: W 1 = (w 11 , w 12 , …, w1n ) T 。

[0023] Preferably, the entropy weight method calculates the weights of indicators by mining the information in the original scores of indicators. According to the variation degree of indicators, the entropy weights of each indicator are calculated using information entropy; the entropy weight method has high precision and strong objectivity, and is more suitable for explaining objective results. The S3 step includes the following steps:

[0024] S3A. Construct the original score matrix: B = (b ij ) m×n ;

[0025] S3B. Perform normalization: C = (c ij ) m×m ;

[0026] S3C. Calculate the indicator information entropy:

[0027] S3D. Calculate the weight vector: W 2 = (w 21 , w 22 , …, w 2n ) T 。

[0028] Preferably, the game weighting method regards the subjective and objective weights as the two sides of the game according to the idea of game theory, analyzes and finds the optimal comprehensive coefficient to minimize the deviation between the two, and obtains the optimal comprehensive weight with the balance of both sides, overcoming the one-sidedness of a single method. The S4 step includes the following steps:

[0029] S4A. Construct the comprehensive weight:

[0030] S4B. Determine the comprehensive coefficient;

[0031] Objective function:

[0032] min(||W - W 1 || 2 + ||W - W 2 || 2 ) = min(||αW 1 + βW 2 - W 1 || 2 + ||αW 1 + βW 2 - W 2 || 2 ),

[0033] Constraint condition:

[0034] Comprehensive coefficient:

[0035]

[0036] S4C. Perform normalization processing:

[0037] S4D. Calculate the optimal comprehensive weight:

[0038] Preferably, the idea of regret theory is to assume that the decision-making process is a comprehensive comparison process. The decision-maker compares the selected option with other options. If the selected option is inferior to other options, regret is felt; if the selected option is superior to other options, joy is felt. In terms of lightning disaster risk assessment, to reduce the losses caused by lightning disasters, there is a risk-averse psychology in the expert evaluation process, and the option to avoid regret will be selected. The advantage of using regret theory to evaluate the lightning disaster risk of scenic spots is that, on the one hand, regret theory inherently has the characteristics of risk aversion, which improves the risk level of lightning disasters in scenic spots to a certain extent and reduces losses; on the other hand, regret theory fully considers the situation of regret aversion and loss aversion in the evaluation process, which conforms to the real psychological situation during evaluation and makes the evaluation result closer to the actual situation. The S5 step includes the following steps:

[0039] S5A. Establish an evaluation index matrix: Q = (q ij ) m×n ;

[0040] S5B. Construct an ideal point matrix: P = (P 1 , P 1 , …, P n );

[0041] S5C. Calculate the utility value matrix: H = (h ij ) m×n ;

[0042] S5D. Determine the regret-joy value matrix: X = (x ij ) m×n ;

[0043] S5E. Calculate the perceived utility matrix: Z = (z ij ) m×n .

[0044] Preferably, the S6 step includes the following steps:

[0045] S6A. Calculate the risk evaluation value:

[0046] S6B. Determine the risk level.

[0047] (III) Beneficial effects

[0048] The present invention provides a method for evaluating the risk of lightning disasters in scenic spots based on game weighting and regret theory, which has the following beneficial effects:

[0049] 1. The game weighting method is used to determine the comprehensive weight of the risk evaluation of lightning disasters in scenic spots, giving full play to the advantages of the improved analytic hierarchy process and entropy weight method for determining subjective and objective weights, making the weights of evaluation indicators more scientific and reasonable.

[0050] 2. The regret theory evaluation method is used to give full play to the advantage of the evaluation result in risk aversion, making the risk level and evaluation value more reasonable and reliable.

[0051] 3. Applying classical risk management theory and relevant technical standards, combined with the risk characteristics of lightning disasters in scenic spots, a risk evaluation index parameter system for lightning disasters is constructed, and a risk level determination standard is proposed, providing a basis for the risk evaluation of lightning disasters in scenic spots.

[0052] 4. According to the components to be improved of each index, the main causes affecting the risk of lightning disasters are found, a targeted improvement plan is formulated, and scientific and reasonable countermeasures are taken to reduce the risk of lightning disasters in scenic spots. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 is a framework diagram of the risk evaluation index parameter system for lightning disasters in scenic spots of the present invention;

[0054] Figure 2 is a flowchart of the steps of the present invention;

[0055] Figure 3 is a schematic diagram of the risk level division and scoring table for lightning disasters in scenic spots of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0056] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0057] Embodiment:

[0058] As Figures 1-3 shown, the embodiment of the present invention provides a method for evaluating the risk of lightning disasters in scenic spots based on game weighting and regret theory, including the following steps:

[0059] S1. Obtaining the risk evaluation index parameters of lightning disasters in scenic spots;

[0060] S2. Determining the subjective weight in the risk evaluation of lightning disasters in scenic spots by the improved analytic hierarchy process;

[0061] S3. Determine the objective weights in the risk assessment of scenic area lightning disasters by the entropy weight method;

[0062] S4. Then, combine the subjective weights and objective weights obtained in the above steps S2 and S3, and use the game weighting method to determine the comprehensive weights in the risk assessment of scenic area lightning disasters;

[0063] S5. Furthermore, couple and evaluate the comprehensive weights in step S4 with the regret theory;

[0064] S6. Finally, obtain the risk assessment value and level of lightning disasters.

[0065] In step S1, there are many factors affecting the risk of scenic area lightning disasters, and there is a certain correlation between them. According to the risk characteristics of different types of scenic areas and in accordance with the classical risk management theory, collect the risk assessment index parameters of lightning disasters from four aspects: hazard-causing factors, disaster-bearing environments, disaster-affecting characteristics, and disaster prevention capabilities, as Figure 1 shown.

[0066] The hazard-causing factor of scenic area lightning disasters is the lightning activity itself. The density of lightning strikes on the ground, the intensity of lightning current, and the historical lightning disasters that have occurred in the scenic area and its surrounding areas are all important indicators characterizing the strength of lightning activity. The disaster-bearing environment is actually the environmental characteristics of the area where the scenic area is located. The high or low soil resistivity, the characteristics of the terrain and landform, and the surrounding environmental conditions are all potential factors affecting the occurrence of lightning disasters. The disaster-affecting characteristics are the characteristic parameters related to lightning disasters of the scenic area itself, mainly including the number of tourists and the visiting duration related to personnel activities, as well as the area, structure, and height related to the characteristics of buildings, and the situation of electronic and electrical systems related to equipment. The disaster prevention capabilities are mainly the technical measures, management measures, and emergency measures taken by the scenic area in lightning protection and disaster reduction, specifically divided into indicators such as the setting, detection, and warning measures of lightning protection devices, as well as management systems, science popularization publicity, emergency plans, evacuation drills, etc.

[0067] Step S2 includes the following steps: The improved analytic hierarchy process uses 3 scales to judge the relative importance between two indicators, significantly reducing the influence of decision-makers' subjective factors, not requiring consistency testing, with a simple process, fast calculation, and being able to meet the accuracy requirements.

[0068] S2A. Construct a comparison matrix: A = (a ij ) n×n ; where: A is the comparison matrix; a ij is the element of the comparison matrix, taking 1 when the i-th indicator is more important than the j-th indicator, -1 vice versa, and 0 when they are equal; n is the number of indicators;

[0069] S2B. Calculate the optimal transfer matrix: R = (r ij ) n×n; where: R is the optimal transfer matrix; r ij is an element of the optimal transfer matrix,

[0070] S2C. Calculate the judgment matrix: D = (d ij ) n×n ; where: D is the judgment matrix; d ij is an element of the judgment matrix,

[0071] S2D. Calculate the weight vector: W 1 = (w 11 , w 12 , …, w 1n ) T ; where: W 1 is the subjective weight vector; w 1i is the subjective weight of the index,

[0072] Step S3 includes the following steps: The entropy weight method calculates the weight of an index by mining the information volume in the original score of the index. According to the variation degree of the index, the entropy weight of each index is calculated using information entropy. The entropy weight method has high precision and strong objectivity, and is more suitable for explaining objective results.

[0073] S3A. Construct the original score matrix: B = (b ij ) m×n ; where: B is the original score matrix; b ij is the element of the original score matrix, that is, the score of the j-th index of the i-th sample; m is the number of samples; n is the number of indexes;

[0074] S3B. Perform normalization: C = (c ij ) m×n ; where: C is the normalized matrix; c ij is the element of the normalized matrix, min(b j ) is the minimum value of the j-th index, and max(b j ) is the maximum value of the j-th index;

[0075] S3C. Calculate the index information entropy: where: s j is the index information entropy; f ij is the proportion of the i-th sample in the j-th index in this index, when f ij = 0, f ij lnf ij = 0;

[0076] S3D. Calculate the weight vector: W 2 = (w 21, w 22 , …, w 2n ) T ; where: W 2 is the objective weight vector; w 2j is the objective weight of the index,

[0077] Step S4 includes the following steps: The game weighting method regards the subjective and objective weights as the two sides of the game according to the idea of game theory, analyzes and finds the optimal comprehensive coefficient to minimize the deviation between the two, obtains the optimal comprehensive weight of the balance between the two, and overcomes the one-sidedness of a single method.

[0078] S4A. Construct the comprehensive weight: where: W is the comprehensive weight vector; α and β are the comprehensive coefficients of W 1 , W 2 respectively;

[0079] S4B. Determine the comprehensive coefficient: Objective function:

[0080] min(||W - W 1 || 2 + ||W - W 2 || 2 ) = min(||αW 1 + βW 2 - W 1 || 2 + ||αW 1 + βW 2 - W 2 || 2 );

[0081] Constraint conditions: where: are the transposed vectors of W 1 , W 2 respectively;

[0082] Comprehensive coefficient:

[0083]

[0084] S4C. Perform normalization processing: where: α * , β * are the optimal comprehensive coefficients of W 1 , W 2 respectively;

[0085] S4D. Calculate the optimal comprehensive weight: where: W * is the optimal comprehensive weight vector; is the optimal comprehensive weight of the index.

[0086] Step S5 includes the following steps: The idea of regret theory is to assume that the decision-making process is a comprehensive comparison process. The decision-maker compares the selected option with other options. If the selected option is inferior to other options, regret is felt; if the selected option is superior to other options, joy is felt. In terms of lightning disaster risk assessment, to reduce the losses caused by lightning disasters, there is a risk-averse psychology in the expert evaluation process, and the option to avoid regret will be selected. The advantage of using regret theory to evaluate the lightning disaster risk of scenic spots is that, on the one hand, regret theory inherently has the characteristic of risk aversion, which improves the risk level of lightning disasters in scenic spots to a certain extent and reduces losses. On the other hand, regret theory fully considers the situation of regret aversion and loss aversion in the evaluation process, which conforms to the real psychological situation during evaluation and makes the evaluation result closer to the actual situation.

[0087] S5A. Establish an evaluation index matrix: Q = (q ij ) m×n ; where: Q is the evaluation index matrix; q ij is the element of the evaluation index matrix, that is, the score of the j-th index of the i-th sample, m is the number of samples, and n is the number of indexes;

[0088] S5B. Construct an ideal point matrix: P = (p 1 , p 2 , …, p n ); where: P is the ideal point matrix, p j is the element of the ideal point matrix, taking the minimum value of the index scores in each sample;

[0089] S5C. Calculate the utility value matrix: H = (h ij ) m×n ; where: H is the utility value matrix; h ij is the element of the effect value matrix, h ij = (q ij ) γ , γ = 0.98;

[0090] S5D. Determine the regret-joy value matrix: X = (x ij ) m×n ; where: X is the regret-joy value matrix; x ij is the element of the regret-joy value matrix, δ = 0.015;

[0091] S5E. Calculate the perceived utility matrix: Z = (z ij ) m×n ; where: Z is the perceived utility matrix; z ij is the element of the perceived utility matrix, z ij = h ij+x ij ;

[0092] Step S6 includes the following steps:

[0093] S6A. Calculate the risk evaluation value: Where: U is the risk evaluation value; u j is the evaluation component of each index, is the average perceived utility of each index,

[0094] S6B. Determine the risk level.

[0095] In order to quantitatively analyze the risk degree of evaluation indicators, referring to the relevant content on risk level division and risk scoring, a percentile system is adopted, and 5 risk level score ranges are divided by the equal-distance score method; according to the method of constructing an ideal point matrix by taking the minimum value of index scores in regret theory, the low risk level is corresponding to the high score range, and a risk level determination standard for scenic area lightning disasters is established, as shown in Figure 3 shown.

[0096] Based on the analysis of the advantages and disadvantages of the improved analytic hierarchy process and entropy weight method in determining the subjective and objective weights of evaluation indicators, the game weighting method is used to determine the comprehensive weight. Using the characteristics of regret theory to avoid risks, a game weighting-regret theory evaluation model is established. Combining the risk evaluation index parameter system and risk level determination standard of scenic area lightning disasters for risk evaluation, and proposing measures to reduce risks, the following conclusions are formed: 1. Using the game weighting method can give full play to the advantages of the subjective and objective weight determination methods, making the weights of evaluation indicators more scientific and reasonable. In the risk evaluation of scenic area lightning disasters, the improved analytic hierarchy process and entropy weight method are respectively used to determine the subjective and objective weights, and the game weighting method is used for synthesis. Through examples, it is verified that the comprehensive weight integrating subjective and objective weights not only considers the positive subjective initiative of experts but also the information volume of the original scores, is more in line with the actual situation and more representative. 2. Using the regret theory evaluation method can give full play to the advantage of avoiding risks in the evaluation results, making the risk level and evaluation value more reasonable and reliable. In the risk evaluation of scenic area lightning disasters, the evaluation results of the regret theory evaluation method are compared with those of the fuzzy comprehensive evaluation method and index mean evaluation method. Through examples, it is verified that the risk levels of the regret theory evaluation method and other methods are consistent, and the risk evaluation value is smaller than that of other methods, which is conducive to reducing unnecessary losses and has certain advantages. 3. Using the game weighting-regret theory evaluation model to carry out risk evaluation can not only determine the risk level and evaluation value but also find out the main factors affecting lightning disaster risks by calculating the components to be improved of each index, understand the risk sources, formulate targeted improvement plans, and take targeted countermeasures, providing guidance for reducing the risk of scenic area lightning disasters.

[0097] Although embodiments of the present invention have been shown and described, those of ordinary skill in the art will appreciate that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for assessing the risk of lightning disasters in scenic areas based on game weighting and regret theory, characterized by: The following steps are involved: S1. Obtaining parameters of lightning disaster risk assessment indicators in scenic areas; S2. Improve the analytic hierarchy process to determine the subjective weights in the risk assessment of lightning disasters in scenic areas; S3, entropy weight method to determine the objective weight in the risk assessment of lightning disasters in scenic areas; S4, then combining the subjective weight and objective weight obtained in the above steps S2 and S3 to determine the comprehensive weight in the risk assessment of lightning disasters in the scenic area using the game weighting method; S5, then coupling the comprehensive weight of step S4 with the regret theory for evaluation; S6. Finally, the lightning disaster risk assessment value and level are obtained.

2. According to claim 1, a method for assessing the risk of lightning disasters in scenic areas based on game weighting and regret theory is characterized by: In step S1, there are many factors that affect the risk of lightning disasters in scenic spots, and there are certain correlations between them. According to the risk characteristics of different types of scenic spots and in accordance with classical risk management theory, lightning disaster risk assessment index parameters are collected from four aspects: disaster-causing factors, disaster-prone environment, disaster-bearing characteristics, and disaster prevention capabilities.

3. The method for assessing the risk of lightning disasters in scenic areas based on game weighting and regret theory according to claim 1 is characterized by: The causative factor of lightning disasters in the scenic area is the lightning activity itself. The density of lightning strikes on the earth, the intensity of lightning current and the lightning disasters that have occurred in the scenic area and its surrounding areas in history are all important indicators that characterize the strength of lightning activity.

4. The method for assessing the risk of lightning disasters in scenic areas based on game weighting and regret theory according to claim 1 is characterized by: The disaster-prone environment is actually the environmental characteristics of the area where the scenic spot is located. The level of soil resistivity, the characteristics of the topography and the surrounding environmental conditions are all potential factors that affect the occurrence of lightning disasters.

5. The method for assessing the risk of lightning disasters in scenic areas based on game weighting and regret theory according to claim 1 is characterized by: The disaster-prone characteristics are the characteristic parameters of the scenic area itself related to lightning disasters, mainly including the number of tourists and the duration of visits related to human activities, the area, structure and height related to the characteristics of buildings, and the electronic and electrical system conditions related to the equipment.

6. The method for assessing the risk of lightning disasters in scenic areas based on game weighting and regret theory according to claim 1 is characterized by: The disaster prevention capabilities mentioned above mainly refer to the technical measures, management measures and emergency measures taken by scenic spots in lightning protection and disaster reduction. They are specifically divided into indicators such as the setting up of lightning protection devices, detection and early warning measures, as well as management systems, popular science publicity, emergency plans, and evacuation drills.

7. The method for assessing the risk of lightning disasters in scenic areas based on game weighting and regret theory according to claim 1 is characterized by: The improved hierarchical analysis method uses three scales to judge the relative importance between two indicators, significantly reducing the influence of subjective factors of decision makers, and does not require consistency inspection. The process is simple, the calculation is fast, and the accuracy requirements can be met. The S2 step includes the following steps: S2A, construct a comparison matrix: A = (a ij ) n×n ; S2B, calculate the optimal transfer matrix: R = (r ij ) n×n ; S2C, calculate the judgment matrix: D = (d ij ) n×n ; S3D, calculate the weight vector: W1 = (w 11 ,w 12 ,…,w 1n ) T .

8. The method for assessing the risk of lightning disasters in scenic areas based on game weighting and regret theory according to claim 1 is characterized by: The entropy weight method calculates the weight of the indicator by mining the information in the original score of the indicator. According to the degree of variation of the indicator, the entropy weight of each indicator is calculated using information entropy. The entropy weight method has high accuracy and strong objectivity, and is more suitable for explaining objective results. The S3 step includes the following steps: S3A, construct the original scoring matrix: B = (b ij ) m×n ; S3B, normalization processing: C = (c ij ) m×n ; S3C, calculation index information entropy: S3D, calculate the weight vector: W2 = (w 21 ,w 22 ,…,w 2n ) T .

9. The method for assessing the risk of lightning disasters in scenic areas based on game weighting and regret theory according to claim 1 is characterized by: The game weighting method regards the subjective and objective weights as the two sides of the game according to the idea of ​​game theory, analyzes and finds the optimal comprehensive coefficient, minimizes the deviation between the two, obtains the optimal comprehensive weight of the balance between the two sides, and overcomes the one-sidedness of a single method. The S4 step includes the following steps: S4A, construct comprehensive weight: S4B. Determine the comprehensive coefficient: Objective function: min(||W-W1||2+||W-W2||2)=min(||αW1+βW2-W1||2+||αW1+βW2-W2||2), Constraints: Comprehensive coefficient: S4C, normalization processing: S4D, calculate the optimal comprehensive weight:

10. The method for assessing the risk of lightning disasters in scenic areas based on game weighting and regret theory according to claim 1, characterized in that: The idea of ​​regret theory is to assume that the decision-making process is a comprehensive comparison process. The decision maker will compare the selected plan with other plans. If the selected plan is inferior to other plans, he will feel regret; if the selected plan is better than other plans, he will feel happy. As far as lightning disaster risk assessment is concerned, in order to reduce the losses caused by lightning disasters, experts have a risk-averse mentality during the evaluation process and will choose plans that avoid regret. The advantage of using regret theory to evaluate the risk of lightning disasters in scenic spots is that, on the one hand, regret theory essentially has the characteristics of risk avoidance, which to a certain extent increases the risk level of lightning disasters in scenic spots and reduces losses; on the other hand, regret theory fully considers the regret avoidance and loss aversion in the evaluation process, which conforms to the real psychological state during the evaluation, making the evaluation results closer to the actual situation. The S5 step includes the following steps: S5A, establish the evaluation index matrix: Q = (q ij ) m×n ; S5B, construct an ideal point matrix: P = (P1, P1, ..., P n ); S5C, calculate the utility value matrix: H = (h ij ) m×n ; S5D, determine the regret-happiness value matrix: X = (x ij ) m×n ; S5E, calculate the perceived utility matrix: Z = (z ij ) m×n .

11. The method for assessing the risk of lightning disasters in scenic areas based on game weighting and regret theory according to claim 1, characterized in that: The step S6 comprises the following steps: S6A. Calculate the risk assessment value: S6B. Determine the risk level.

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