Bacterial foraging with PSO algorithm and its application on attribute reduction. (1st January 2012) - Zhao, Qingshan; Meng, Guoyan; Wu, Zhijian
Attribute reduction is the important part in rough set theory. Enlightened by bacterial foraging processing, this paper combines the idea of bacterial foraging algorithm with particle swarm optimisation and proposes a new algorithm-BFPSO algorithm. In this algorithm, the chemotaxis of bacterial foraging can guide the particles to evolve towards much better direction, in turn, the convergence speed and optimisation capabilities are increasing by using PSO. The proposed algorithm is applied to the attribute reduction. Experiments show that attribute reduction based on BFPSO algorithm achieve much better result in optimisation capabilities by comparing with other algorithms, and show that the better minimal attribute reduction can been found by the algorithm.