Statistical-based Multi-Criteria Decision Making Approach for prediction of the grade of an Institution in NAAC.

Dey, Pabitra Kumar; Ghosh, Dipendra Nath; MONDAL, SUKARNA D.E.Y.

doi:10.1504/ijmor.2023.10054189

Cited by 1 publication

(2 citation statements)

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“…Second, TOPSIS is used to select the best alternative strategy for ranking the teams. Performance-based analysis is studied among IPL batsmen in seasons I (2008), II (2009), and III (2010) using statistical multicriteria decision-making [22]. ey concluded that international players performed well in season II, but their performance varied from season to season.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Multicriteria group decision method studied in [18] gives a practical way to evaluate a team's success while producing consistent performance ratings. Multicriteria decision tree approach [19] can classify all-rounders in the Indian Premier League for accurately and efficiently classifying data based on the output of players. It is also shown how multicriteria decision tree method provided a good image of the players in several categories, including performer, batting all-rounder, bowling all-rounder, and underperformer, aiding franchisee owners in picking allrounders in the auction and compensating them depending on their performance.…”

Section: Literature Reviewmentioning

confidence: 99%

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Comparative Analysis of TOPSIS and TODIM for the Performance Evaluation of Foreign Players in Indian Premier League

et al. 2022

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Sports officials, players, and fans are concerned about overseas player rankings for the IPL auction. These rankings are becoming progressively essential to investors when premium leagues are commercialized. The decision-makers of the Indian Premier League choose cricketers based on their own experience in sports and based on performance statistics on several criteria. This paper presents a scientific way to rank the players. Our research examines and contrasts different multicriteria decision-making algorithms for ranking foreign players under various criteria to assess their performance and efficiency. The paper uses three MCDM algorithms, TOPSIS, TODIM, and NR-TOPSIS, for foreign players ranking in the Indian Premier League. Our analysis is limited to the batsmen and bowlers only. We perform the analysis using Python language, a popular high-level programming language. Finally, we perform a sensitivity analysis to determine the stability of each method when the weights of the criterion or the value of a parameter was changed. Our analysis exhibits the superiority of TODIM over TOPSIS and NR-TOPSIS.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%