T
Tapan Senapati
Researcher at Vidyasagar University
Publications - 75
Citations - 1684
Tapan Senapati is an academic researcher from Vidyasagar University. The author has contributed to research in topics: Computer science & Fuzzy logic. The author has an hindex of 17, co-authored 32 publications receiving 697 citations. Previous affiliations of Tapan Senapati include Southwest University.
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Fermatean fuzzy sets
Tapan Senapati,Ronald R. Yager +1 more
TL;DR: A Fermatean fuzzy TOPSIS method is established to fix multiple criteria decision-making problem and an interpretative example is stated in details to justify the elaborated method and to illustrate its viability and usefulness.
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Picture fuzzy Dombi aggregation operators: Application to MADM process
TL;DR: A model for picture fuzzy Dombi aggregation operators to solve multiple attribute decision making (MADM) methods in an updated way is developed and at the end of the study a practical application of the deducted decision over investment alternatives is reported.
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Fermatean fuzzy weighted averaging/geometric operators and its application in multi-criteria decision-making methods
Tapan Senapati,Ronald R. Yager +1 more
TL;DR: A viable case for picking the specific spots for home construction is given and an approach for MCDM problem in light of new operators under Fermatean fuzzy condition is proposed.
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Some New Operations Over Fermatean Fuzzy Numbers and Application of Fermatean Fuzzy WPM in Multiple Criteria Decision Making
Tapan Senapati,Ronald R. Yager +1 more
TL;DR: A Fermatean fuzzy weighted product model is developed to solve the multi-criteria decision-making problem and an illustrative example of selecting a suitable bridge construction method is given to demonstrate its practicability and effectiveness.
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Pythagorean fuzzy Dombi aggregation operators and its applications in multiple attribute decision‐making
TL;DR: A model to remedy the multiple attribute decision‐making issues under Pythagorean fuzzy environment is built up and a realistic instance is stated to substantiate the created model and to exhibit its applicability and viability.