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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국정보처리학회 JIPS(Journal of Information Processing Systems) JIPS(Journal of Information Processing Systems) 제13권 제4호
- 발행연도
- 2017.1
- 수록면
- 1,000 - 1,013 (14page)
이용수
초록· 키워드
오류제보하기
Clustering is a NP-hard problem that is used to find the relationship between patterns in a given set ofpatterns. It is an unsupervised technique that is applied to obtain the optimal cluster centers, especially inpartitioned based clustering algorithms. On the other hand, cat swarm optimization (CSO) is a new metaheuristicalgorithm that has been applied to solve various optimization problems and it provides better resultsin comparison to other similar types of algorithms. However, this algorithm suffers from diversity and localoptima problems. To overcome these problems, we are proposing an improved version of the CSO algorithmby using opposition-based learning and the Cauchy mutation operator. We applied the opposition-basedlearning method to enhance the diversity of the CSO algorithm and we used the Cauchy mutation operator toprevent the CSO algorithm from trapping in local optima. The performance of our proposed algorithm wastested with several artificial and real datasets and compared with existing methods like K-means, particleswarm optimization, and CSO. The experimental results show the applicability of our proposed method.
목차
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참고문헌 (27)
참고문헌 신청
A. J. Sahoo / 2014 / Advances in Signal Processing and Intelligent Recognition Systems / Springer : 429 ~ 437
A. K. Jain / 2010 / Data clustering : 50 years beyond K-means / Pattern Recognition Letters 31 (8) : 651 ~ 666
B. Santosa / 2009 / Cat swarm optimization for clustering / Proceedings of IEEE International Conference of Soft Computing and Pattern Recognition (SOCPAR'09) : 54 ~ 59
C. A. Murthy / 1996 / In search of optimal clusters using genetic algorithms / Pattern Recognition Letters 17 (8) : 825 ~ 832
C. Y. Tsai / 2011 / Particle swarm optimization with selective particle regeneration for data clustering / Expert Systems with Applications 38 (6) : 6565 ~ 6576
A. K. Jain / 2010 / Data clustering : 50 years beyond K-means / Pattern Recognition Letters 31 (8) : 651 ~ 666
B. Santosa / 2009 / Cat swarm optimization for clustering / Proceedings of IEEE International Conference of Soft Computing and Pattern Recognition (SOCPAR'09) : 54 ~ 59
C. A. Murthy / 1996 / In search of optimal clusters using genetic algorithms / Pattern Recognition Letters 17 (8) : 825 ~ 832
C. Y. Tsai / 2011 / Particle swarm optimization with selective particle regeneration for data clustering / Expert Systems with Applications 38 (6) : 6565 ~ 6576
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