Interval valued fuzzy matrix-based decision making for machine learning algorithms. Issue 3 (11th February 2021)

• Record Type: Journal Article
• Authors: Bhatnagar, Priya; Ohri, Kriti; Sukheja, Deepak
• Is Part Of: International journal of computational systems engineering. Volume 6:Issue 3(2021)
• Page Start: 134
• Page End: 142
• Publication Date: 2021-02-11
• Subjects: interval valued fuzzy matrix -- decision making -- algebra; Computer science -- Periodicals; Electronic data processing -- Periodicals; System analysis -- Periodicals; 003.3
• Languages: English
• ISSNs: 2046-3391

Abstract

Decision making is very important in machine learning or imparting artificial intelligence into machines that work upon the traditional logic theory. It is a process that helps a machine to think like a human being and for a human being to ease his/her difficult decision-making process. Real world problems related to decision making contain uncertainty in data which cannot be very precise as per our choice; as it is seen that the interval valued fuzzy logic deals greatly with such imprecise data and gives the best outcome. This paper presents a multi criteria decision making approach using interval valued fuzzy logic through a new operator and a new algorithm which is based on various parameters of satisfaction of a buyer who wish to buy a certain item provides a great choice of satisfaction with a certain result. Finally, with the help of a case study based on a significant survey the proposed method is described.