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Pre-training analysis for student's placement training using hendecagonal fuzzy number with similarity measure

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  • M. Revathi
  • M. Valliathal

Abstract

Multi-criteria group decision-making approaches with fuzzy theory are trendy in the area of decision science. Frequently decision-makers express their judgment linguistically. This study aims to categorise the student's basic knowledge level in order to provide pre-placement training for the students in the placement. A method is constructed using several linguistic values with different weights using the fuzzy number grading system. An algorithm for fuzzy multi-criteria group decision-making (FMCGDM) is proposed with the notion of hendecagonal fuzzy number (HDFN) and symmetric hendecagonal fuzzy number (symmHDFN). Also, complex proportional assessment (COPRAS) method is used for group decision-making approach, to assess the performance of students in the pre-placement training. Based on the report generated, the college can arrange varying levels of training using fuzzy decision theory.

Suggested Citation

  • M. Revathi & M. Valliathal, 2021. "Pre-training analysis for student's placement training using hendecagonal fuzzy number with similarity measure," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 39(4), pages 451-476.
    • Handle: RePEc:ids:ijsoma:v:39:y:2021:i:4:p:451-476
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