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This table 4 shows that the values of Medical sciences in WASPAS method Weighted normalized outcome matrix 1. Students’ views of learning, academics self, perspectives of the environment, and social self of students professors’ impressions of their students Table 3 Medical sciences on weight in all weight ages same weight

Table 4 This table 4 shows that the values of Medical sciences in WASPAS method Weighted normalized outcome matrix 1. Students’ views of learning, academics self, perspectives of the environment, and social self of students professors’ impressions of their students Table 3 Medical sciences on weight in all weight ages same weight

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Steps 1 The decision matrix X which shows the performances of different alternatives with respect to various criteria is formed. Step 2: The decision matrix is normalized. Beneficial and non-beneficial criteria are normalized
Steps 1 The decision matrix X which shows the performances of different alternatives with respect to various criteria is formed. Step 2: The decision matrix is normalized. Beneficial and non-beneficial criteria are normalized
TABLE 1. Medical sciences in Data Set This table 1 shows the Male interns at the value of dataset for Medical sciences in WASPAS method Alternative: Male students, Female students, and Female interns. Evaluation Option: Students' views of learning, academics self. perspectives of the environment, and social self of students’ professors' impressions of their students 3. ANALYSIS AND DISCUSSION New entropy, divergence and simuarity for LViFSos Actions are proposed. MCDM Classical WASFAS method for handling problems As an extension, the classical WASPAS method For space-valued intuitionist fuzzy contexts Suitable. [11] Approach IT2FSs operators, classical WASPAS Some changes in methodology and weighting criteria A new process for calculating based on Scale weight In the calculation process, [12] By visual features of satellite images of Managed Edge Detection Algorithms A new MCDM problem dedicated to adaptive selection We create. Also, using the neutrosopic WASPASS method. [13] WASPAS methodology for final assessment of 3PL providers is used. of the classical WASPAS method Steps WASPAS-CRITIC integrated with IT2FS Used to expand the approach. [14] The WASPAS method is a weighted sum model and A combination of the weighted product model, and it ranks the alternatives thoroughly is used of Critic and WASPASS methods A new composition-based This approach to decision- making literature This is the main contribution of the article. [15] The rest is structured as follows. A Introduction WASPAS Methodology Section 'WASPASS Methodology’ is given. 'Danger Identification and In the section on criteria weights’, risks and Criterion weights are identified. [16] A number of hesitant criteria make the decision Weighted total product to solve problems A based on the assessment (WASPAS) approach An integrated method has been developed. Ambiguous Information. This method is typical WASPAS Approach and weighting criteria some advances in the process of clans based on [17] Evolution of WASPAS used to solve the problem considered the method is given below. The original crisp WASPAS is the first extension of the structured method under interval-valued intuitionist fuzzy set context [18] of the use of cubic intuitionist numbers basically an extension of this paper is used WASPAS method to solve ¢ large number of DM problems. [19] They collaborate Together the assessment process is SWARA and WASPAS Techniques. Alternate based on SWARA and WASPAS In evaluating and prioritizing routes Experts participated. [20]
TABLE 1. Medical sciences in Data Set This table 1 shows the Male interns at the value of dataset for Medical sciences in WASPAS method Alternative: Male students, Female students, and Female interns. Evaluation Option: Students' views of learning, academics self. perspectives of the environment, and social self of students’ professors' impressions of their students 3. ANALYSIS AND DISCUSSION New entropy, divergence and simuarity for LViFSos Actions are proposed. MCDM Classical WASFAS method for handling problems As an extension, the classical WASPAS method For space-valued intuitionist fuzzy contexts Suitable. [11] Approach IT2FSs operators, classical WASPAS Some changes in methodology and weighting criteria A new process for calculating based on Scale weight In the calculation process, [12] By visual features of satellite images of Managed Edge Detection Algorithms A new MCDM problem dedicated to adaptive selection We create. Also, using the neutrosopic WASPASS method. [13] WASPAS methodology for final assessment of 3PL providers is used. of the classical WASPAS method Steps WASPAS-CRITIC integrated with IT2FS Used to expand the approach. [14] The WASPAS method is a weighted sum model and A combination of the weighted product model, and it ranks the alternatives thoroughly is used of Critic and WASPASS methods A new composition-based This approach to decision- making literature This is the main contribution of the article. [15] The rest is structured as follows. A Introduction WASPAS Methodology Section 'WASPASS Methodology’ is given. 'Danger Identification and In the section on criteria weights’, risks and Criterion weights are identified. [16] A number of hesitant criteria make the decision Weighted total product to solve problems A based on the assessment (WASPAS) approach An integrated method has been developed. Ambiguous Information. This method is typical WASPAS Approach and weighting criteria some advances in the process of clans based on [17] Evolution of WASPAS used to solve the problem considered the method is given below. The original crisp WASPAS is the first extension of the structured method under interval-valued intuitionist fuzzy set context [18] of the use of cubic intuitionist numbers basically an extension of this paper is used WASPAS method to solve ¢ large number of DM problems. [19] They collaborate Together the assessment process is SWARA and WASPAS Techniques. Alternate based on SWARA and WASPAS In evaluating and prioritizing routes Experts participated. [20]
Figure | shows the Alternative: Male students, Female students, and Female interns. Evaluation Option: Students’ views of learning, academics self, perspectives of the environment, and social self of students’ professors' impressions of their students
Figure | shows the Alternative: Male students, Female students, and Female interns. Evaluation Option: Students’ views of learning, academics self, perspectives of the environment, and social self of students’ professors' impressions of their students
TABLE 2. Medical sciences in Performance value This table 2 shows that the values of Medical sciences in WASPAS method. Find the pair wise comparison value for Students’ views of learning, academics self, perspectives of the environment, and social self of students professors’ impressions of their students
TABLE 2. Medical sciences in Performance value This table 2 shows that the values of Medical sciences in WASPAS method. Find the pair wise comparison value for Students’ views of learning, academics self, perspectives of the environment, and social self of students professors’ impressions of their students
This table 6 shows that the values of Medical sciences in Preference Score 1, Preference Score 2, WASPAS Coefficient, RANK For Medical sciences using WASPAS. Find the pair wise comparison value for Students’ views of learning, academics self, perspectives of the environment, and social self of students professors’ impressions of their students
This table 6 shows that the values of Medical sciences in Preference Score 1, Preference Score 2, WASPAS Coefficient, RANK For Medical sciences using WASPAS. Find the pair wise comparison value for Students’ views of learning, academics self, perspectives of the environment, and social self of students professors’ impressions of their students
This figure 2 shows that from the- Medical sciences in Preference Score | result it is seen that Students’ perception of atmosphere = 0.924979 and is got the first value whereas is the Students’ perception of learning = 0.882084 got is having the lowest value. This figure 2 shows that from the Medical sciences in Preference Score 2 result it is seen that Students’ perception of atmosphere = 0.923979 and is got the first value whereas is the Students’ perception of learning = 0.877328 got is having the lowest value.
This figure 2 shows that from the- Medical sciences in Preference Score | result it is seen that Students’ perception of atmosphere = 0.924979 and is got the first value whereas is the Students’ perception of learning = 0.882084 got is having the lowest value. This figure 2 shows that from the Medical sciences in Preference Score 2 result it is seen that Students’ perception of atmosphere = 0.923979 and is got the first value whereas is the Students’ perception of learning = 0.877328 got is having the lowest value.
‘his figure 3 shows that from the result it is seen that Students’ perception of atmosphere = 0.924479 and is got the first alue whereas is the Students’ perception of learning = 0.879706 got is having the lowest value. This figure 4 shows that from the result it is seen that Students’ perception of atmosphere and is got the first rank whereas is the Students’ perception of learning got is having the lowest rank.
‘his figure 3 shows that from the result it is seen that Students’ perception of atmosphere = 0.924479 and is got the first alue whereas is the Students’ perception of learning = 0.879706 got is having the lowest value. This figure 4 shows that from the result it is seen that Students’ perception of atmosphere and is got the first rank whereas is the Students’ perception of learning got is having the lowest rank.
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