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

Abstract. Functional Magnetic Resonance Imaging (fMRI) data is collected ceaselessly during brain research, which implicates some important information. It need to be extracted and translated to intelligible knowledge. In this paper, we attempt to extract multi-knowledge from fMRI data using rough set approach. 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. We illustrate some results using our approach, which is helpful for cognition research.

• Type: Conference
• Year: 2008
• Where: HAIS
• Authors: Hongbo Liu, Ajith Abraham, Hong Ye
• Keywords: Artificial Intelligence, Functional Magnetic Resonance Imaging, HAIS 2008, Rough Set, Rough Set Approach