A fuzzy neural network with fuzzy impact grades

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Song, Hengjie, Miao, Chunyan, Shen, Zhiqi, Miao, Yuan and Lee, Bushun (2009) A fuzzy neural network with fuzzy impact grades. Neurocomputing, 72 (13-15). pp. 3098-3122. ISSN 0925-2312


Fuzzy rule derivation is often difficult and time-consuming,and requires expert knowledge. Thiscreates a common bottleneck in fuzzy system design. In order to solve this problem, many fuzzy systems that automatically generate fuzzy rules from numerical data have been proposed. In this paper, we propose a fuzzy neural network based on mutual subsethood(MSBFNN)and its fuzzy rule identification algorithms. In our approach, fuzzy rules are described by different fuzzy sets. For each fuzzy set representing a fuzzy rule, the universe of discourse is defined as the summation of weighted membership grades of input linguistic terms that associate with the given fuzzy rule. In this manner, MSBFNN fully considers the contribution of input variables to the joint firing strength of fuzzy rules. Afterwards, the proposed fuzzy neural network quantifies the impacts of fuzzy rules on the consequent parts by fuzzy connections based on mutual subsethood. Furthermore, to enhance the knowledge representation and interpretation of the rules, a linear transformation from consequent parts to output is incorporated into MSBFNN so that higher accuracy can be achieved. In the parameter identification phase, the back propagation algorithm is employed, and proper linear transformation is also determined dynamically. To demonstrate the capability of the MSBFNN, simulations in different areas including classification, regression and time series prediction are conducted. The proposed MSBFNN shows encouraging performance when benchmarked against other models.

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Item type Article
URI https://vuir.vu.edu.au/id/eprint/4604
DOI 10.1016/j.neucom.2009.03.009
Official URL http://www.sciencedirect.com/science/article/pii/S...
Subjects Historical > Faculty/School/Research Centre/Department > School of Engineering and Science
Historical > FOR Classification > 0801 Artificial Intelligence and Image Processing
Historical > SEO Classification > 970108 Expanding Knowledge in the Information and Computing Sciences
Keywords ResPubID18616, fuzzy neural network, mutual subsethood, fuzzy rule identification
Citations in Scopus 23 - View on Scopus
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