Abstract
In this paper, we present a new algorithm of swarm intelligence, namely, Cat Swarm Optimization (CSO). CSO is generated by observing the behaviors of cats, and composed of two sub-models, i.e., tracing mode and seeking mode, which model upon the behaviors of cats. Experimental results using six test functions demonstrate that CSO has much better performance than Particle Swarm Optimization (PSO).
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© 2006 Springer-Verlag Berlin Heidelberg
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Chu, SC., Tsai, Pw., Pan, JS. (2006). Cat Swarm Optimization. In: Yang, Q., Webb, G. (eds) PRICAI 2006: Trends in Artificial Intelligence. PRICAI 2006. Lecture Notes in Computer Science(), vol 4099. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36668-3_94
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DOI: https://doi.org/10.1007/978-3-540-36668-3_94
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36667-6
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