Paper Info
Title
Evidential Reasoning Using Extended Fuzzy Dempster-Shafer Theory For Handling Various Facets Of Information Deficiency
Abstract
This work investigates the problem of combining deficient evidence for the purpose of quality assessment. The main focus of the work is modeling vagueness, ambiguity, and local nonspecificity in information within a unified approach. We introduce an extended fuzzy Dempster-Shafer scheme based on the simultaneous use of fuzzy interval-grade and interval-valued belief degree (IGIB). The latter facilitates modeling of uncertainties in terms of local ignorance associated with expert knowledge, whereas the former allows for handling the lack of information on belief degree assignments. Also, generalized fuzzy sets can be readily transformed into the proposed fuzzy IGIB structure. The reasoning for quality assessment is performed by solving nonlinear optimization problems on fuzzy Dempster-Shafer paradigm for the fuzzy IGIB structure. The application of the proposed inference method is investigated by designing a reasoning scheme for water quality monitoring and validated through the experimental data available for different sampling points in a water distribution network. (C) 2011 Wiley Periodicals, Inc.
Year
DOI
Venue
2011
10.1002/int.20491
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
Field
DocType
Volume
Data mining,Neuro-fuzzy,Defuzzification,Fuzzy classification,Fuzzy set operations,Fuzzy logic,Fuzzy set,Artificial intelligence,Evidential reasoning approach,Dempster–Shafer theory,Machine learning,Mathematics
Journal
26
Issue
ISSN
Citations 
8
0884-8173
10
PageRank 
References 
Authors
0.66
35
6
Name
Order
Citations
PageRank
Farzad Aminravan1162.93
Rehan Sadiq236430.26
Mina Hoorfar3185.54
Manuel J. Rodríguez4273.76
Alex Francisque5292.34
Homayoun Najjaran67822.13