Title: Bio-inspired technology systems and data analysis methods for classification and subsequent decision making intended for automated systems

Authors: Sheenam; D. Mishra; A. Rath; D. Zhang; N.P. Mahalik

Addresses: Department of Industrial Technology, California State University, Fresno, USA ' Department of Computer Science and Engineering, Institute of Technical Education and Research (ITER), Siksha 'O' Anusandhan (SOA), Bhubaneswar, India ' Computer Science and Engineering, Dhaneswar Rath Institute of Engineering and Management Studies, Cuttack, India ' Department of Industrial Technology, California State University, Fresno, USA ' Department of Industrial Technology, California State University, Fresno, USA

Abstract: The objective of this research is to study various types of recently developed data mining algorithm and contribute a new method. We have reviewed biological data analysis methods, which will lead us to foresee if the set of proposed algorithms can help in analysing data in areas such as automation and safety. In this research we have addressed clustering. By establishing some problems, we identified the solutions through developed algorithm. The algorithms are developed around high dimensional gene expression dataset. We have shown that the proposed rough principal component analysis (R-PCA) scheme is capable of handling the high dimensionality. We have also reviewed and formulated a validation index for the measurement of quality. Our analysis considers GA framework. The paper presents introduction and review, methods, results, discussion, and future work in appropriate order.

Keywords: automation; safety; control; bio-inspired computation; biological data analysis; decision making; artificial intelligence; data mining; clustering algorithms; gene expression data; rough PCA: principal component analysis; R-PCA; bioinformatics.

DOI: 10.1504/IJCVR.2016.079398

International Journal of Computational Vision and Robotics, 2016 Vol.6 No.4, pp.381 - 398

Received: 02 Aug 2014
Accepted: 05 Sep 2014

Published online: 28 Sep 2016 *

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