This paper provides an agent genetic algorithm based on bacteria foraging strategy (BFOA-L) as the feature selection method, and presents the combined method of link-like agent structure and neural network based on bacteria foraging algorithm (BFOA). It introduces the bacteria foraging (BF) action into the feature selection and utilizes the neural network structure achieve fuzzy logic inference, so that the weights with no definite physical meaning in traditional neural network are endowed with the physical meaning of fuzzy logic inference parameters. Furthermore, to overcome the defects of traditional optimization methods, it applies the agent link-like competition strategy into the global optimization process to raise the convergence accuracy. The curve tracing test results show that this algorithm has good stability and high accuracy. © Springer-Verlag Berlin Heidelberg 2011.
CITATION STYLE
Liang, D., Zheng, W., & Li, Y. (2011). Bacteria Foraging Based Agent Feature Selection Algorithm. In Communications in Computer and Information Science (Vol. 134, pp. 581–588). https://doi.org/10.1007/978-3-642-18129-0_89
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