Interval valued fuzzy matrix-based decision making for machine learning algorithms Online publication date: Thu, 25-Feb-2021
by Priya Bhatnagar; Kriti Ohri; Deepak Sukheja
International Journal of Computational Systems Engineering (IJCSYSE), Vol. 6, No. 3, 2021
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.
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