Abstract
A novel method of data fitting via chaotic ant swarm (CAS) is presented in this paper. Through the construction of a suitable function, the problem of data fitting can be viewed as that of parameter optimization, and then the CAS is used to search the parameter space so as to find the optimal estimations of the system parameters. To investigate the performances of the CAS, the CAS is compared with the particle swarrn optimization (PSO) on two test problems. Simulation results indicate that the CAS achieves better performances. © Springer-Verlag Berlin Heidelberg 2006.
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CITATION STYLE
Li, Y. Y., Li, L. X., Wen, Q. Y., & Yang, Y. X. (2006). Data fitting via chaotic ant swarm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4222 LNCS-II, pp. 180–183). Springer Verlag. https://doi.org/10.1007/11881223_23
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