Multi-knowledge extraction algorithm using Group Search Optimization for brain dataset analysis

Author

Zhengqiong Zhu ; Zongmei Wang ; Tiancheng Li ; Xingyu Wang ; Hongbo Liu ; Hassanien, Aboul Ella ; Wanqing Yang

Author_Institution

Sch. of Inf., Dalian Maritime Univ., Dalian, China

fYear

2015

fDate

11-13 March 2015

Firstpage

1891

Lastpage

1896

Abstract

Knowledge is formed by a kind of mapping from the condition space to the decision space in rough set. This paper presents multi-knowledge extraction approaches with fuzzy population algorithms. The Group Search Optimization (GSO) and Particle Swarm Optimization (PSO) are compared. GSO not only has the rapid convergence speed, but also has low time complexity, especially for high dimensional datasets. We use the multi-knowledge extraction algorithm based on GSO to analyze the data of brain cognition datasets. The experimental results illustrate our algorithm is very promising to seek for the relationship between the active brain regions and stimuli.

Keywords

brain; cognition; computational complexity; convergence; fuzzy set theory; knowledge acquisition; medical computing; particle swarm optimisation; rough set theory; search problems; GSO; PSO; active brain regions; brain cognition datasets; brain dataset analysis; condition space; convergence speed; decision space; fuzzy population algorithms; group search optimization; high dimensional datasets; multiknowledge extraction algorithm; particle swarm optimization; rough set; stimuli; time complexity; Companies; Data mining; Information technology; Integrated circuits; Brain Science; Fuzzy Population; Group Search Optimization; Multi-knowledge; Rough Set;

fLanguage

English

Publisher

ieee

Conference_Titel

Computing for Sustainable Global Development (INDIACom), 2015 2nd International Conference on

Conference_Location

New Delhi

Print_ISBN

978-9-3805-4415-1

Type

conf

Filename

7100573