A new monotonicity index for fuzzy rule-based systems
Contribuinte(s) |
[Unknown] |
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Data(s) |
01/01/2014
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Resumo |
A search in the literature reveals that mathematical conditions (usually sufficient conditions) for the Fuzzy Inference System (FIS) models to satisfy the monotonicity property have been developed. A monotonically-ordered fuzzy rule base is important to maintain the monotonicity property of an FIS. However, it may difficult to obtain a monotonically-ordered fuzzy rule base in practice. We have previously introduced the idea of fuzzy rule relabeling to tackle this problem. In this paper, we further propose a monotonicity index for the FIS system, which serves as a metric to indicate the degree of a fuzzy rule base fulfilling the monotonicity property. The index is useful to provide an indication whether a fuzzy rule base should (or should not) be used in practice, even with fuzzy rule relabeling. To illustrate the idea, the zero-order Sugeno FIS model is exemplified. We add noise as errors into the fuzzy rule base to formulate a set of non-monotone fuzzy rules. As such, the metric also acts as a measure of noise in the fuzzy rule base. The results show that the proposed metric is useful to indicate the degree of a fuzzy rule base fulfilling the monotonicity property. |
Identificador | |
Idioma(s) |
eng |
Publicador |
IEEE |
Relação |
http://dro.deakin.edu.au/eserv/DU:30070583/pang-anewmonotonicity-2014.pdf http://dro.deakin.edu.au/eserv/DU:30070583/pang-anewmonotonicity-evid-2014.pdf http://dro.deakin.edu.au/eserv/DU:30070583/pang-evid-conffuzzieee-2014.pdf http://www.dx.doi.org/10.1109/FUZZ-IEEE.2014.6891555 |
Direitos |
2014, Institute of Electrical and Electronics Engineers |
Palavras-Chave | #Fuzzy inference system #fuzzy rule base #monotonicity index |
Tipo |
Conference Paper |