Title: Interval valued fuzzy matrix-based decision making for machine learning algorithms

Authors: Priya Bhatnagar; Kriti Ohri; Deepak Sukheja

Addresses: Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, 500090, Telangana, India ' Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, 500090, Telangana, India ' Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, 500090, Telangana, India

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.

Keywords: interval valued fuzzy matrix; decision making; algebra.

DOI: 10.1504/IJCSYSE.2021.113262

International Journal of Computational Systems Engineering, 2021 Vol.6 No.3, pp.134 - 142

Received: 18 Jun 2020
Accepted: 10 Aug 2020
Published online: 25 Feb 2021 *

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