Bacterial foraging with PSO algorithm and its application on attribute reduction Online publication date: Mon, 07-May-2012
by Qingshan Zhao; Guoyan Meng; Zhijian Wu
International Journal of Innovative Computing and Applications (IJICA), Vol. 4, No. 2, 2012
Abstract: 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.
Online publication date: Mon, 07-May-2012
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Innovative Computing and Applications (IJICA):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com