An intelligent feature selection method based on the Bacterial Foraging Algorithm

This paper puts forward an agent genetic algorithm based on bacteria foraging strategy (BFOA-L) as the feature selection method. The algorithm introduces the bacteria foraging (BF) behavior, and integrates the neural network and link agent structure to achieve fuzzy logic reasoning, so that the weights with no definite physical meaning in traditional neural network are endowed with the physical meaning of fuzzy logic reasoning parameters. The algorithm can maintain the diversity of the agent, so as to achieve satisfactory global optimization precision. The test result shows that this algorithm has good stability, little time complexity and high recognition accuracy.