Fuzzy Matrix Theory based Decision Making for Machine Learning
Department of Mathematics, Dr. A. P. J. Abdul Kalam University Indore (M.P) India
* Author to whom correspondence should be addressed.
Journal of Engineering Research and Sciences, Volume 1, Issue 6, Page # 13-20, 2022; DOI: 10.55708/js0106003
Keywords: Decision Making, Fuzzy Logic Technique, Fuzzy Sets, Max-Min Composition, Fuzzy Matrix Multiplication
Received: 18 February 2022, Revised: 22 April 2022, Accepted: 03 June 2022, Published Online: 24 June 2022
APA Style
Shah, J. A. (2022). Fuzzy Matrix Theory based Decision Making for Machine Learning. Journal of Engineering Research and Sciences, 1(6), 13–20. https://doi.org/10.55708/js0106003
Chicago/Turabian Style
Shah, Javaid Ahmad. “Fuzzy Matrix Theory based Decision Making for Machine Learning.” Journal of Engineering Research and Sciences 1, no. 6 (June 1, 2022): 13–20. https://doi.org/10.55708/js0106003.
IEEE Style
J. A. Shah, “Fuzzy Matrix Theory based Decision Making for Machine Learning,” Journal of Engineering Research and Sciences, vol. 1, no. 6, pp. 13–20, Jun. 2022, doi: 10.55708/js0106003.
The Fuzzy set theory has numerous real-life applications in almost every field like artificial intelligence, pattern recognition, medical diagnosis etc. There are so many techniques used for solving decision-making problems given by various researchers from time to time. To be able to make consistent and correct choices is the essence of any decision process pervade with uncertainty. Fuzzy matrix theory plays an important role in scientific development under uncertain conditions. Nowadays there are huge varieties of mobile phones with varying features available in the market. Everyone wants to purchase such a mobile phone which has as many features as possible within it but under his/her budget. This has become an important issue in this modern era where everyone wants to have the most preferred mobile handsets for himself/herself as compared to others. So, in this paper, the Fuzzy matrix approach is used in a decision-making problem where a number of buyers can be able to choose their preferred mobile phones with varying features.
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