TY  - JOUR
EP  - 321
A1  - Abraham, A.
A1  - Vasant, P.
A1  - Bhattacharya, A.
Y1  - 2008///
SN  - 19316828
TI  - Neuro-fuzzy approximation of multi-criteria decision-making QFD methodology
ID  - scholars488
SP  - 301
N1  - cited By 9
VL  - 16
JF  - Springer Optimization and Its Applications
PB  - Springer International Publishing
N2  - 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.
AV  - none
UR  - 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
ER  -