Title: Multi-criteria decision-making for purchasing cell phones using machine learning approach

Authors: Kriti Shree; Sarita Mohanty; Sachi Nandan Mohanty

Addresses: School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India ' Center for Post-Graduate Studies, OUAT, Bhubaneswar, Odisha, India ' School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India

Abstract: The process of selecting and purchasing cell phones is a multi-criteria decision-making (MCDM) problem with conflicting and diverse objectives. This study discusses various techniques involved in selecting and purchasing a cell phone by using machine learning approach. The responses of the participants were sought through a questionnaire which gave them different options with regard to the latest features available in a cell phone. Seven independent input variables - cost, battery backup, rear camera, weight, size, memory and operating system, were provided to the participants to elicit their responses. Each of the input variables was measured on a scale expressed in linguistic terms as low, medium and high. Mamdani approach, traditional fuzzy reasoning tool (FLC) and neuro-fuzzy system (ANFIS) were used to design three input and one output processes. The back-propagation algorithm formed the basis for application of the neuro-fuzzy system. Two traditional fuzzy reasoning tools - the artificial neural network (ANN) approach and the neuro-fuzzy system, were used to arrive at more accurate understanding of the process of selecting a cell phone for personal use.

Keywords: cell phone selection; multi-criteria decision-making; MCDM; artificial neural network; ANN; approach neuro-fuzzy system ANFIS; fuzzy reasoning tool; FLC.

DOI: 10.1504/IJDSRM.2017.090348

International Journal of Decision Sciences, Risk and Management, 2017 Vol.7 No.3, pp.190 - 218

Received: 08 Aug 2016
Accepted: 07 Apr 2017

Published online: 13 Mar 2018 *

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