Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
409633 | Neurocomputing | 2015 | 11 Pages |
Abstract
In this paper, a novel method, called intelligent Takagi–Sugeno Modeling (iTaSuM), for identifying the structure and parameters of T–S fuzzy system is developed based on heterogeneous cuckoo search algorithm (HeCoS) to overcome the drawbacks that classical cuckoo search algorithm. HeCoS is a new variant of cuckoo search algorithm with heterogeneous searching strategies based on the quantum mechanism. Through the experimental analysis, we demonstrate that the proposed algorithm has a balance between exploration and exploitation. Comparing with other existing methods, we achieve that iTaSuM can generate good fuzzy system model with high accuracy and strong generalization ability.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Xueming Ding, Zhenkai Xu, Ngaam J. Cheung, Xiaohui Liu,