Extracting Multi-knowledge from fMRI Data through Swarm-Based Rough Set Reduction

Authors:
Hongbo Liu;Ajith Abraham;Hong Ye
Affiliations:
School of Computer Science, Dalian Maritime University, Dalian, China 116026;Centre for Quantifiable Quality of Service in Communication Systems, Norwegian University of Science and Technology, Trondheim, Norway;School of Computer Science, Dalian Maritime University, Dalian, China 116026
Venue:
HAIS '08 Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems
Year:
2008

Citing 3
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Abstract

With the development of brain science, various kinds of new methods and techniques are applied. A mass of Functional Magnetic Resonance Imaging (fMRI) data is collected ceaselessly, which implicates very important information. The useful information need be extracted and translated to intelligible knowledge, which is exigent to develop some methods to analyze them effectively and objectively. In this paper, we attempt to extract multi-knowledge from fMRI Data using rough set approach. We introduce the data pre-processing workflow and methods. A rough set reduction approach is presented based on particle swarm optimization algorithm, which discover the feature combinations in an efficient way to observe the change of positive region as the particles proceed through the search space. The approach supports multi-knowledge extraction. We also illustrate some results using our approach, which is helpful for cognition research.