Citation

Wee, Yit Yin and Cheah, Wooi Ping and Tan, Shing Chiang and Wee, Kuok Kwee (2019) An evaluation of the role of fuzzy cognitive maps and Bayesian belief networks in the development of causal knowledge systems. Journal of Intelligent & Fuzzy Systems, 37 (2). pp. 1905-1920. ISSN 10641246

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Abstract

Fuzzy cognitive maps (FCM) and Bayesian belief networks (BBN) are two of the most frequently used causal knowledge frameworks for modelling, representing and reasoning about causal knowledge. In this paper, an evaluation of their different roles in the engineering process of developing causal knowledge systems is conducted, based on their inherent features. The evaluation criteria adopted in this research are understandability, usability, modularity, scalability, expressiveness, inferential capability, rigour, formality and preciseness. All of these are commonly used to evaluate the strengths and weaknesses of traditional knowledge representation frameworks. These criteria are used to reveal the fundamental characteristics of FCM and BBN. The findings of this study show that FCM is more appropriate for use in modelling causal knowledge, whereas BBN is more superior in model representation and inference. This study deepens the understanding of the role of FCM and BBN in the development of causal knowledge systems.

Item Type:	Article
Uncontrolled Keywords:	Evaluation
Subjects:	T Technology > TD Environmental technology. Sanitary engineering > TD895-899 Industrial and factory sanitation
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	04 May 2021 15:04
Last Modified:	04 May 2021 15:04
URII:	http://shdl.mmu.edu.my/id/eprint/8654

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