Knowledge-based genetic algorithm for multidimensional data clustering

Purnomo, Muhammad Ridwan Andi and Saleh, Chairul and Lagaida, Reny Lituhayu and Hassan, Azmi (2014) Knowledge-based genetic algorithm for multidimensional data clustering. Applied Mechanics and Materials, 606. pp. 277-280. ISSN 1660-9336

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Abstract

In this paper, a new approach of genetic algorithm called knowledge-based Genetic Algorithm (KBGA-Clustering) is proposed for multidimensional data clustering. Basically, this method adopts knowledge of what called as appropriate cluster centre for a fixed number of kcluster. The chromosome which has inappropriate genes will be penalised with maximum value to prohibit it in the next generation. The experimental result is also provided for KBGA-Clustering and Genetic Algorithm-Clustering (GA-Clustering) to present the performance. Based on the observation, KBGA-Clustering presents better performance and more optimum solution compared to conventional GA-Clustering.

Item Type:	Article (Journal)
Additional Information:	6946/37531
Uncontrolled Keywords:	K-means; clustering; genetic algorithm; knowledge-based.
Subjects:	Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) > T175 Industrial research. Research and development
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User:	Dr Azmi Bin Hassan
Date Deposited:	04 Aug 2014 09:52
Last Modified:	06 Sep 2017 12:03
URI:	http://irep.iium.edu.my/id/eprint/37531

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