relation: https://khub.utp.edu.my/scholars/488/
title: Neuro-fuzzy approximation of multi-criteria decision-making QFD methodology
creator: Abraham, A.
creator: Vasant, P.
creator: Bhattacharya, A.
description: This chapter demonstrates how a neuro-fuzzy approach could produce outputs of a further-modified multi-criteria decision-making (MCDM) quality function deployment (QFD) model within the required error rate. The improved fuzzified MCDM model uses the modified S-curve membership function (MF) as stated in an earlier chapter. The smooth and flexible logistic membership function (MF) finds out fuzziness patterns in disparate level-of-satisfaction for the integrated analytic hierarchy process (AHP-QFD model. The key objective of this chapter is to guide decision makers in finding out the best candidate-alternative robot with a higher degree of satisfaction and with a lesser degree of fuzziness. © Springer Science + Business Media, LLC 2008.
publisher: Springer International Publishing
date: 2008
type: Article
type: PeerReviewed
identifier:   Abraham, A. and Vasant, P. and Bhattacharya, A.  (2008) Neuro-fuzzy approximation of multi-criteria decision-making QFD methodology.  Springer Optimization and Its Applications, 16.  pp. 301-321.  ISSN 19316828     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84976463038&doi=10.1007%2f978-0-387-76813-7_12&partnerID=40&md5=92fb8a20e07b9b8bab459a966f8a0cba
relation: 10.1007/978-0-387-76813-7₁₂
identifier: 10.1007/978-0-387-76813-7₁₂