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An Evolving-Construction Scheme for Fuzzy Systems
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DOI：10.1109/TFUZZ.2010.2047949.png)
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This paper proposes an evolving-construction scheme for fuzzy systems (ECSFS). ECSFS begins with a simple fuzzy system and evolves its structure by adding more fuzzy terms and rules to achieve a better accuracy in a greedy way. An interesting feature of ECSFS is that it is able to automatically locate mathematically meaningful points, such as the extremum and inflexion points of the approximated function one by one, and then adds fuzzy terms based on these points. Fuzzy systems with such extreme points, like their fuzzy terms, are more efficient than other fuzzy systems by using the same number of fuzzy rules. As a result, ECSFS often achieves a better accuracy for fuzzy-system identification compared with the previous methods when using the same number of fuzzy rules. A number of simulation results are given to illustrate the advantages of the proposed scheme.
Keyword:
Evolving construction
function approximation
greedy algorithm
incremental learning
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11.9
论文数:
5.0K
被引数:
2.9W
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