Implementation and comparison of contemporary data clustering techniques for a multi-compressor system: a case study

Authors:
Gursewak S. Brar;Yadwinder S. Brar;Yaduvir Singh
Affiliations:
Department of Electrical Engineering, Baba Banda Singh Bahadur Engineering College, Fathegarh Sahib, Punjab, India;Department of Electrical Engineering, Giani Zail Singh College of Engineering and Technology, Bathinda, Punjab, India;Department of Electrical and Instrumentation Engineering, Thapar University, Patiala, Punjab, India
Venue:
WSEAS Transactions on Systems and Control
Year:
2007

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Abstract

This paper gives the implementation and deployment of fuzzy clustering algorithm applied to a process control data along with its comparison to various other clustering algorithms. In this paper, the analysis is carried out for the data as obtained from a multi-compressor system based on the factor of keeping the maximum weighted square error at the minimum level. Also, this paper consists of an algorithm, which groups the data according to fuzzy clustering, considering the intermediate values between zero and one. The paper also outlines the comparison among other clustering algorithms on the basis of various validation parameters there by telling us the importance of fuzzy clustering, which considers all the ambiguity in data to be a part of n-clusters, giving an extra attribute of membership function.