Abstract
The paper presents a novel search algorithm named adaptive tabu search (ATS). The algorithm has been applied to enhance the learning process of neural networks. The paper presents a new neuro-tabu-fuzzy (NTF) control structure to demonstrate the capability of the ATS algorithm. The algorithm is general and can be applied to various problems including machine learning, optimization, etc. Our proposed algorithm and controller nicely stabilize the single- and double-inverted pendulum systems. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Sujitjorn, S., & Khwan-on, S. (2006). Learning control via neuro-tabu-fuzzy controller. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4251 LNAI-I, pp. 833–840). Springer Verlag. https://doi.org/10.1007/11892960_100
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