JOURNAL ARTICLE

Constructing manufacturing-environmental model in Bayesian belief networks for assembly design decision support through fuzzy cognitive maps

Wooi Ping CheahKyoung‐Yun KimHyung Jeong YangMan Sun KimJeongsik Kim

Year: 2009 Journal:   International Journal of Intelligent Information and Database Systems Vol: 3 (1)Pages: 3-3   Publisher: Inderscience Publishers

Abstract

This paper deals with the introduction of the Bayesian belief network (BBN) for the representation and reasoning about manufacturing environmental knowledge which captures the interactions between manufacturing-environmental factors and assembly design decision (ADD) criteria. BBN is used because it has a sound mathematical foundation, expressive representation scheme, powerful reasoning capability, efficient evidence propagation mechanism and proven track record in industry-scale applications. Unfortunately, the construction of conditional probability tables (CPTs) is both tedious and unnatural. Hence, fuzzy cognitive map (FCM) is introduced for knowledge acquisition because it is simple and user friendly. We also propose a method for the conversion of FCM into BBN.

Keywords:
Computer science Fuzzy cognitive map Bayesian network Fuzzy logic Artificial intelligence Knowledge representation and reasoning Representation (politics) Machine learning Scheme (mathematics) Bayesian probability Conditional probability Neuro-fuzzy Fuzzy control system

Metrics

4
Cited By
1.52
FWCI (Field Weighted Citation Impact)
30
Refs
0.89
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Cognitive Science and Mapping
Physical Sciences →  Computer Science →  Artificial Intelligence
Multi-Criteria Decision Making
Social Sciences →  Decision Sciences →  Management Science and Operations Research
Cognitive Computing and Networks
Physical Sciences →  Computer Science →  Artificial Intelligence

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