Thermal physiology safety evaluation index construction method based on entropy-VIKOR model

Abstract

The invention provides a thermal physiological safety evaluation index construction method based on an entropy-VIKOR model, and the method comprises the steps: introducing an entropy-# imgabs0 # model to evaluate the thermal stress and physiological state safety of a person in a high-temperature and high-humidity environment, carrying out the normalization processing of physiological parameters, calculating the weight value of an index through an entropy weight method, and carrying out the calculation of the weight value of the index, determining a positive ideal solution and a negative ideal solution of a to-be-evaluated index, calculating a group benefit value and an individual regret value of the to-be-evaluated index, finally calculating a benefit ratio Q value of the to-be-evaluated index, and evaluating the thermal physiological status of the personnel in the high-temperature and high-humidity environment through the Q value. According to the method, the thermal physiological state of the operator in the high-temperature and high-humidity environment can be evaluated in real time, corresponding measures are taken in time, so that the harm of environmental thermal stress to the human body is reduced, the safety of the operator is guaranteed, simple and easy-to-measure human body comprehensive physiological stress evaluation indexes are established, and the method has profound academic significance and application value.

Description

Technical Field

[0001] The present application relates to the technical field of safety assessment, and in particular to a method for constructing a thermal physiological safety evaluation index based on an entropy-VIKOR model. Background Art

[0002] Heat stress evaluation indicators play a certain guiding role in evaluating the thermal physiological safety status of workers. Some evaluation indicators are established based on environmental parameters, and there are relatively few comprehensive indicators proposed from physiological parameters. How to evaluate the thermal physiological status of people in high temperature and high humidity environments through physiological parameters, establish simple and easy-to-measure comprehensive physiological stress evaluation indicators for the human body, and evaluate the physiological safety status of the human body in real time so as to take corresponding measures in time to reduce the harm of environmental thermal stress to the human body and ensure the safety of workers has far-reaching academic significance and application value. Summary of the invention

[0003] This application aims to use entropy- Model establishment of comprehensive physiological stress evaluation index of human body under high temperature and high humidity environment ,pass Evaluate the thermal physiological status of personnel in high temperature and high humidity environments to reduce the harm of environmental thermal stress to the human body and ensure the safety of workers.

[0004] This application adopts the following technical solutions: A method for constructing a thermal physiological safety evaluation index based on an entropy-VIKOR model comprises the following steps: (1) obtaining physiological parameters and normalizing the physiological parameters, wherein the physiological parameters include one or more of eardrum temperature, oral temperature, average skin temperature and heart rate; (2) Determine the weight value of the indicator through the entropy weight method; (3) Determine the positive ideal solution and negative ideal solution of the indicator to be evaluated; (4) Calculate the group benefit value of the indicator to be evaluated and individual regret value ; (5) Calculate the benefit ratio of the indicator to be evaluated Value, through The value is used to evaluate the thermal physiological safety status of personnel.

[0005] In the method for constructing the thermal physiological safety evaluation index based on the entropy-VIKOR model as described above, in step (1), the normalized calculation formula is as follows: (1.1); Where: ——No. Under the indicator Project evaluation value; ——No. Under the indicator The original value of each item; ——No. The optimal interval of the original value of each indicator; ——No. The original value of each indicator is the upper limit of danger.

[0006] As described above, in the method for constructing the thermal physiological safety evaluation index based on the entropy-VIKOR model, the calculation formula for determining the index weight by the entropy weight method in step (2) is as follows: existing Items to be evaluated, Indicators to be evaluated form the original data matrix : (1.2); No. Under the indicator The proportion of project index values : (1.3); No. The entropy value of the index : (1.4); No. Entropy weight of an indicator : (1.5).

[0007] As described above, the method for constructing the thermal physiological safety evaluation index based on the entropy-VIKOR model, the calculation formulas for the positive ideal solution and the negative ideal solution in step (3) are as follows: Positive ideal solution: (1.6); Negative ideal solution: (1.7); Where: ——No. The positive ideal solution of the index; ——No. Negative ideal solution of an indicator.

[0008] As described above, in the method for constructing the thermal physiological safety evaluation index based on the entropy-VIKOR model, in step (4), the group benefit value and individual regret value The calculation formula is as follows: (1.8); (1.9).

[0009] As described above, in the method for constructing the thermophysiological safety evaluation index based on the entropy-VIKOR model, in step (5), the benefit ratio The value is calculated as follows: (1.10); In the formula , , , , is the decision mechanism coefficient, When , it tends to be more like individual regretful decision; When making decisions, they tend to make group benefits; When making decisions, choose a compromise approach.

[0010] According to the method for constructing the thermal physiological safety evaluation index based on the entropy-VIKOR model as described above, the optimal range of the tympanic temperature is 35.5-37.4°C, and the upper limit of the danger level is 38°C.

[0011] As described above, the method for constructing the thermal physiological safety evaluation index based on the entropy-VIKOR model has an optimal range of average skin temperature of 32.8-33.8°C and an upper limit of danger of 37.6°C.

[0012] According to the method for constructing the thermophysiological safety evaluation index based on the entropy-VIKOR model as described above, the optimal range of oral temperature is 36.3-37.2°C, and the upper limit of danger is 37.5°C.

[0013] According to the method for constructing the thermal physiological safety evaluation index based on the entropy-VIKOR model as described above, the optimal range of heart rate is 60-95 bpm, and the upper limit of danger is 146 bpm.

[0014] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a method for constructing a thermal physiological safety evaluation index based on the entropy-VIKOR model, introducing the entropy- The model evaluates the heat stress and physiological state safety of personnel in high temperature and high humidity environments. First, the physiological parameters are normalized, and then the weight values ​​of the indicators are calculated by the entropy weight method. Then, the positive ideal solution and the negative ideal solution of the indicator to be evaluated are determined, and then the group benefit value and the individual regret value of the indicator to be evaluated are calculated. Finally, the benefit ratio Q value of the indicator to be evaluated is calculated. The thermal physiological state of personnel in high temperature and high humidity environments is evaluated by the Q value. The thermal physiological state of workers in high temperature and high humidity environments can be evaluated in real time, and corresponding measures can be taken in time to reduce the harm of environmental thermal stress to the human body and ensure the safety of workers. This application establishes a simple and easy-to-measure comprehensive physiological stress evaluation index for the human body, which has far-reaching academic significance and application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for describing the embodiments are briefly introduced below.

[0016] Figure 1 is a box plot of the physiological parameter weights of the subjects in the embodiment of the present application; Figure 2 This is a QI value diagram of light labor intensity in the embodiment of the present application; Figure 3 It is a QI value diagram of moderate labor intensity in the embodiment of the present application; Figure 4 It is a QI value diagram of heavy labor intensity in the embodiment of the present application; Figure 5 is a diagram showing the relationship between QI and thermal sensation voting in an embodiment of the present application; Figure 6 is a relationship diagram between QI and thermal comfort voting in the embodiment of the present application; Figure 7 is a relationship diagram between QI and PHSI in the embodiment of the present application; Figure 8 It is a relationship diagram between QI and four environmental indicators in the embodiment of the present application. DETAILED DESCRIPTION

[0017] A method for constructing a thermal physiological safety evaluation index based on an entropy-VIKOR model comprises the following steps: (1) obtaining physiological parameters and normalizing the physiological parameters, wherein the physiological parameters include one or more of eardrum temperature, oral temperature, average skin temperature and heart rate; (2) Determine the weight value of the indicator through the entropy weight method; (3) Determine the positive ideal solution and negative ideal solution of the indicator to be evaluated; (4) Calculate the group benefit value of the indicator to be evaluated and individual regret value ; (5) Calculate the benefit ratio of the indicator to be evaluated Value, through The value is used to evaluate the thermal physiological safety status of personnel.

[0018] The specific steps are as follows: (1) Normalization (1.1) Where: ——No. Under the indicator Project evaluation value; ——No. Under the indicator The original value of each item; ——No. The optimal interval of the original value of the index ——No. The original value of the indicator is the upper limit of danger (2) Determine indicator weights using entropy weight method existing Items to be evaluated, Indicators to be evaluated form the original data matrix : (1.2) No. Under the indicator The proportion of project index values : (1.3) No. The entropy value of the index : (1.4) No. Entropy weight of an indicator : (1.5) (3) Determine the positive ideal solution and negative ideal solution of the indicator to be evaluated Positive ideal solution: (1.6) Negative ideal solution: (1.7) Where: ——No. Positive ideal solution of index ——No. Negative ideal solution of index (4) Calculate the group benefit value of the indicator to be evaluated and individual regret value

[0019] (1.8) (1.9) (5) Calculate the benefit ratio of the indicator to be evaluated value (1.10) In the formula , , , , is the decision mechanism coefficient, When , it tends to be more like individual regretful decision; When making decisions, they tend to make group benefits; When making decisions, choose a compromise approach. The value is generally taken as 0.5 to balance the decision risk of decision makers. The value range is [0,1]. The closer the benefit ratio value is to 0, the better the status of the evaluation object is. The closer the benefit ratio value is to 1, the worse the status of the evaluation object is.

[0020] The entropy weight method is an objective weighting method. Entropy is originally a thermodynamic concept and was introduced into information theory by Shamon. Entropy weight is used to characterize the relative intensity of various indicators in the evaluation system of the target system. The entropy weight method uses the entropy value to find the weight of the evaluation indicator. Generally speaking, the smaller the information entropy of the indicator, the greater the variation of its value and the greater the amount of information, the greater its weight, and vice versa. The multi-criteria compromise solution ranking method (Vlsekriterijumska Optimizacija IKompromis-no Resenine) is a compromise multi-attribute decision-making method proposed by Opricovic (abbreviated as VIKOR model). It is based on the Lpmetric aggregation function. The basic idea is to first define the "positive ideal solution" and "negative ideal solution" of each evaluation indicator, thereby obtaining the positive ideal solution and the negative ideal solution, and then rank the solutions under the conditions of acceptable advantages and stable decision-making process according to the degree of closeness between each evaluation solution and the ideal solution, and then evaluate the advantages and disadvantages of each evaluation solution. The model takes into account the subjective preferences of decision makers and compromises between maximizing group benefits and minimizing individual regrets to obtain a compromise solution. The model has been widely used in engineering technology, finance and economics, etc. by virtue of its more reasonable multi-attribute decision-making method and comprehensive indicator system. The model was used to select and rank composite materials for dental restorations. The results showed that this method is of great significance for enhancing the decision-making process in the biomedical field. Kumar et al. used entropy- The model demonstrated that ACR-2 alloy composites can optimize overall performance and are recommended for structural and tribological applications. Mojaver et al. used entropy- The model ranked the fuel performance of different biomasses (pine sawdust, peanut shells, straw, rice husks, eucalyptus, sunflower seed husks, and sugarcane bagasse) and the results showed that eucalyptus performed best. Malekian and Azarnivand used entropy- The model ranks the flood risk priorities in Shemshak Basin, Iran. The results show that the highest priority of flood potential is the largest hydrological unit Sh2 in Shemshak. This method has the potential to be used in different fields related to watershed management.

[0021] This application introduces entropy- The model evaluates the heat stress and physiological status safety of personnel in high temperature and high humidity environments, using entropy- Model establishment of comprehensive physiological stress evaluation index of human body under high temperature and high humidity environment , according to the results of variance analysis of physiological parameters, Based on the physiological parameters: eardrum temperature, oral temperature, average skin temperature, and heart rate, the real-time weights of the four physiological parameters were obtained by the entropy weight method, and were determined by fitting with the environmental index and heat stress evaluation index proposed in previous studies. By Evaluate the thermal physiological status of personnel in high temperature and high humidity environments to reduce the harm of environmental thermal stress to the human body and ensure the safety of workers.

[0022] Specific examples of comprehensive evaluation of physiological status: The entropy-VIKOR model can timely evaluate the physiological safety status of personnel in high temperature and high humidity environments. In order to facilitate the evaluation of the influence of ambient temperature, ambient humidity, labor intensity and labor time on the subjects, the average value of the physiological parameters measured at each working condition time point is used, with a total of 288 sets of valid experimental data. The comfort value of the physiological parameter, that is, the positive ideal solution, is an interval number, and all physiological parameters need to be normalized according to formula (1.1).

[0023] The normal range of eardrum temperature is 35.5-37.4℃, 37.5-37.9℃ is considered low fever, and above 38℃ requires further examination. Therefore, the comfort range of eardrum temperature is set at 35.5-37.4℃, and the upper limit of danger is set at 38℃.

[0024] The average skin temperature comfort range is 32.8-33.8℃, the relatively dangerous range is 37.6-38.2℃, and the very dangerous range is 38.2-38.5℃. Therefore, the comfortable range of the average skin temperature is set to 32.8-33.8℃, and the upper limit of the danger is set to 37.6℃.

[0025] The normal range of oral temperature is 36.3-37.2℃. WHO and NIOSH recommend that for personnel working in high temperature and high humidity environments, the internal core temperature of the body should not exceed 38℃, or the oral temperature should not exceed 37.5℃ during work. Therefore, this application sets the comfortable range of oral temperature to 36.3-37.2℃, and the upper limit of danger to 37.5℃.

[0026] The heart rate safety range is 60-95bpm, the safer range is 96-120bpm, the normal range is 121-145bpm, and the dangerous range is 146-180bpm. Therefore, this application sets the heart rate comfort range to 60-95bpm and the dangerous upper limit to 146 bpm.

[0027] The comfort range limits of the above four physiological parameters are shown in Table 1.

[0028] Table 1 Physiological parameter limits

[0029] The following is an example of a set of physiological parameter data: (1) The upper limit of danger, experimental measurement value, and comfort value constitute the test items, and form the original data matrix with the above four physiological parameters (from left to right: eardrum temperature, average skin temperature, oral temperature, heart rate):

[0030]

[0031] (2) Calculate the weight of the indicator according to formulas (1.2) to (1.5):

[0032] Depend on It can be seen that the weights of the eardrum temperature, average skin temperature, oral temperature, and heart rate of this group are 0.2695, 0.2575, 0.2365, and 0.2365, respectively. The weight calculation process of the remaining data is the same as above. Figure 1As shown, the results show that the weight ranges of eardrum temperature, average skin temperature, oral temperature and heart rate are 0.1519-0.4211, 0.1935-0.3452, 0.1604-0.4269 and 0.1348-0.3391 respectively. Among them, the mean value shows that the weight of the average skin temperature of the subjects is higher than that of the other three physiological parameters, indicating that the average skin temperature of the subjects is more affected by the high temperature and humidity environment and labor intensity than the eardrum temperature, oral temperature and heart rate.

[0033] (3) Determine the positive ideal solution and the negative ideal solution. After the physiological parameters form the original data matrix and are normalized, the closer the value is to 1, the closer the physiological parameter is to the comfort zone. Therefore, the positive ideal solution takes the value of 1 and the negative ideal solution takes the value of 0, as shown in the following formula. Positive ideal solution:

[0034] Negative ideal solution:

[0035] (4) According to formulas (1.8) and (1.9), the group benefit value and individual regret value of the physiological parameters of this group are calculated as shown below.

[0036]

[0037]

[0038] (5) Calculate the Q value of this group of experimental data according to formula (1.10), as shown in the following formula.

[0039]

[0040] The Q value calculation process of the remaining experimental data is the same as above and will not be repeated here. Based on the weights, four physiological parameters are considered, which can evaluate the thermal physiological state of workers in high temperature and high humidity environments in real time, and is comprehensive. Therefore, it is defined as a comprehensive physiological stress evaluation index , The calculation of is shown in formula (1.11).

[0041] (1.11) The value range is [0,1], 1 represents very dangerous, 0 represents absolutely safe, that is, the closer the value is to 0, the safer the physiological state of the human body is, and the closer the value is to 1, the more dangerous the physiological state of the human body is. The numerical quantitative expression of the physiological safety state of people in high temperature and high humidity environments is intuitive.

[0042] Simulate workers in 48 working conditions Value Figures 2 to 4shown.

[0043] The subjects were subjected to light labor simulation at an ambient temperature of 32°C and 34°C. At this time, the environmental heat stress was low, the human body was in a state of thermal equilibrium, and the environmental humidity had no significant effect on the heat stress of the human body. The value is relatively stable. When the ambient temperature is 36℃ or 38℃, the heat load on the human body increases, and the increase in ambient humidity reduces the evaporative heat dissipation efficiency of the human skin surface, causing heat accumulation in the body and worsening the thermal physiological state. The value increases. Moderate and heavy labor intensity increases the body's metabolic rate and heat production. Under the same environmental conditions, The value increased. Under extreme conditions, the subjects' The value is 1, which is in an extremely dangerous state. In summary, the worse the environmental conditions, the higher the labor intensity, and the longer the working time, the worse the thermal physiological state of the human body. The higher the value.

[0044] Verification of indicator validity: In order to verify the rationality and effectiveness of the comprehensive evaluation indicators established, this application research Relationship with thermal sensation, thermal comfort and PHSI. Thermal sensation and thermal comfort reflect the feeling and comfort state of the human body in a thermal environment, while PHSI reflects the heat stress of the human body.

[0045] (1) Relationship between QI and thermal sensation Relationship with thermal sensation Figure 5 As shown, with The increase in thermal sensation voting value increases accordingly. In a high temperature and high humidity environment, when the subject's own thermal sensation is poor, his physiological parameters are also in a poor state. According to the fitting relationship, the comprehensive physiological stress evaluation index There is a linear relationship with the subjective thermal sensation vote, R 2 =0.8357, the goodness of fit is average. The test was conducted in an environmental chamber, and different subjects worked in different temperature and humidity environments and with different labor intensities. Their thermal adaptability was different, and the human body's thermal psychological reactions were different. The above factors may lead to a low goodness of fit.

[0046] (2) Relationship between QI and thermal comfort Relationship with thermal comfort Figure 6 shown.

[0047] As QI increases, the thermal sensation score gradually decreases. In a high temperature and high humidity environment, when the subject feels uncomfortable, his physiological parameters are also in a poor state. According to the fitting relationship, there is a linear relationship between the comprehensive physiological safety evaluation index QI and the subjective thermal sensation vote, R 2=0.828, goodness of fit is average. Thermal comfort is the same as thermal sensation, which is a thermal psychological reaction. Different subjects working in different temperature and humidity environments and with different labor intensities have different thermal adaptability and individual differences. 2 The value of .

[0048] (3) Relationship between QI and PHSI PHSI is an improvement on the Physiological Strain Index (PSI) proposed by Moran. PHSI replaces the difficult-to-measure rectal temperature with the oral temperature, which is easy to measure in the experiment. It is easier to obtain the heat stress index value in time and get the tolerance response of the personnel in time. The calculation formula is shown in formula (1.12) (1.12) Among them, 39.5 represents the upper limit of oral temperature 39.5℃; 180 represents the upper limit of heart rate 180bpm. The heat stress intensity grades corresponding to PHSI are shown in Table 2.

[0049] Table 2 PHSI thermal stress intensity classification

[0050] The relationship between QI and PHSI is as follows Figure 7 As shown in the figure, as the QI value increases, the PHSI value increases accordingly, indicating that the value of the physiological parameters of the personnel deviates from the ideal state and the intensity of the thermal stress is gradually increasing. 2 =0.901, with a high goodness of fit, indicating that both can well reflect the heat stress state of personnel. When the QI value reaches 0.8-1.0, the heat stress intensity value of the subjects is between 8-11.9. At this time, the subjects are under severe or very severe heat stress and are in an extremely dangerous physiological state. 2 =0.901, QI integrates four physiological parameters, but PHSI only considers two physiological parameters, thus underestimating the influence of other physiological parameters, thus affecting R 2 The values ​​have a certain impact.

[0051] (4) Relationship between QI and environmental index The relationship between QI and effective temperature ET, temperature and humidity index THI, heat index HI, and sultry index SSI is as follows: Figure 8 As shown in the figure, as the QI value increases, the values ​​of the four environmental indices increase accordingly, which indicates that as the ambient temperature and humidity increase, the comfort level of personnel gradually decreases, and the values ​​of physiological parameters gradually deviate from the ideal state. QI and the four environmental indices are polynomially related, and R 2They are all high, indicating that QI can well evaluate the physiological state of people in high temperature and high humidity environment, and QI is significantly affected by ambient temperature and humidity. The specific fitting equation and goodness of fit are shown in Table 3.

[0052] Table 3 Fitting relationship between QI and ET, THI, HI, and SSI

[0053] QI evaluation mechanism: High temperature and high humidity environment can cause discomfort or even death to workers, so the assessment of such environmental conditions is particularly important. According to the fitting relationship between QI and various indicators in "(3) Relationship between QI and PHSI" and "(4) Relationship between QI and environmental index", it is found that QI has the highest goodness of fit with summer heat index SSI, R 2 =0.9749, but after consulting the data, it was found that the classification of these four environmental indicators cannot be well used for early warning of QI. Therefore, this application uses PHSI as the standard to predict QI. The numerical range of PHSI [-1,4] is defined as the safe range; the numerical range of PHSI (4,6] is defined as the tolerance range; the numerical range of PHSI (6,12] is defined as the dangerous range. Therefore, the classification of QI is shown in Table 4.

[0054] Table 4 QI classification

[0055] The present invention provides a method for constructing a thermal physiological safety evaluation index based on the entropy-VIKOR model, introducing the entropy- The model evaluates the heat stress and physiological state safety of personnel in high temperature and high humidity environments. First, the physiological parameters are normalized, and then the weight values ​​of the indicators are calculated by the entropy weight method. Then, the positive ideal solution and the negative ideal solution of the indicator to be evaluated are determined, and then the group benefit value and the individual regret value of the indicator to be evaluated are calculated. Finally, the benefit ratio Q value of the indicator to be evaluated is calculated. The thermal physiological state of personnel in high temperature and high humidity environments is evaluated by the Q value. The thermal physiological state of workers in high temperature and high humidity environments can be evaluated in real time, and corresponding measures can be taken in time to reduce the harm of environmental thermal stress to the human body and ensure the safety of workers. This application establishes a simple and easy-to-measure comprehensive physiological stress evaluation index for the human body, which has far-reaching academic significance and application value.

[0056] As described above, one or more implementation methods are provided in combination with specific contents, and the specific implementation of the present invention is not limited to these descriptions. Any similarity or similarity with the method, structure, etc. of the present invention, or any technical deduction or replacement based on the concept of the present invention, shall be regarded as the protection scope of the present invention.

Claims

1. A method for constructing a thermal physiological safety evaluation index based on the entropy-VIKOR model, characterized in that: The following steps are involved: (1) obtaining physiological parameters and normalizing the physiological parameters, wherein the physiological parameters include one or more of eardrum temperature, oral temperature, average skin temperature and heart rate; (2) Determine the weight value of the indicator through the entropy weight method; (3) Determine the positive ideal solution and negative ideal solution of the indicator to be evaluated; (4) Calculate the group benefit value of the indicator to be evaluated and individual regret value ; (5) Calculate the benefit ratio of the indicator to be evaluated Value, through The value is used to evaluate the thermal physiological safety status of personnel.

2. The method for constructing a thermophysiological safety evaluation index based on the entropy-VIKOR model according to claim 1, characterized in that: In step (1), the normalized calculation formula is as follows: （1.1）； Where: ——No. Under the indicator Project evaluation value; ——No. Under the indicator The original value of each item; ——No. The optimal interval of the original value of each indicator; ——No. The original value of each indicator is the upper limit of danger.

3. The method for constructing a thermophysiological safety evaluation index based on the entropy-VIKOR model according to claim 2, characterized in that: The calculation formula for determining the indicator weight using the entropy weight method in step (2) is as follows: existing Items to be evaluated, Indicators to be evaluated form the original data matrix : （1.2）； No. Under the indicator The proportion of project index values : （1.3）； No. The entropy value of the index : （1.4）； No. Entropy weight of an indicator : （1.5）。 4. The method for constructing a thermophysiological safety evaluation index based on the entropy-VIKOR model according to claim 1, characterized in that: The calculation formulas for the positive ideal solution and the negative ideal solution in step (3) are as follows: Positive ideal solution: （1.6）； Negative ideal solution: （1.7）； Where: ——No. The positive ideal solution of the index; ——No. Negative ideal solution of an indicator.

5. The method for constructing a thermophysiological safety evaluation index based on the entropy-VIKOR model according to claim 4, characterized in that: In step (4), the group benefit value and individual regret value The calculation formula is as follows: （1.8）； （1.9）。 6. The method for constructing a thermophysiological safety evaluation index based on the entropy-VIKOR model according to claim 5, characterized in that: In step (5), the benefit ratio The value is calculated as follows: （1.10）； In the formula , , , , is the decision mechanism coefficient, When , it tends to be more like individual regretful decision; When making decisions, they tend to make group benefits decisions; When making decisions, choose a compromise approach.

7. The method for constructing a thermophysiological safety evaluation index based on the entropy-VIKOR model according to claim 1, characterized in that: The optimal range of tympanic temperature is 35.5-37.4℃, and the upper dangerous limit is 38℃.

8. The method for constructing a thermophysiological safety evaluation index based on the entropy-VIKOR model according to claim 1, characterized in that: The optimal range of average skin temperature is 32.8-33.8℃, and the upper dangerous limit is 37.6℃.

9. The method for constructing a thermophysiological safety evaluation index based on the entropy-VIKOR model according to claim 1, characterized in that: The optimal range of oral temperature is 36.3-37.2℃, and the upper dangerous limit is 37.5℃.

10. The method for constructing a thermophysiological safety evaluation index based on the entropy-VIKOR model according to claim 1, characterized in that: The optimal heart rate range is 60-95bpm, and the upper dangerous limit is 146 bpm.

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