(A) tabu-search-based algorithm for clustering = 타부탐색기법에 기초한 군집방안의 모색

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This thesis considers a clustering problem for pattern recognition where clustering plays a role of furnishing information in a unsupervised learning approach to be used for designing a pattern classifier when any sufficient information on the associated data structure is not available. For the problem two algorithms are exploited. One is a Tabu Search algorithm and the other one is a Tabu-Search-based algorithm. Because Tabu Search is not stick to a local optimum solution, the Tabu Search algorithm can obtain better solution than traditional algorithms, including the K-means algorithm, which stick to local optimum solutions. This Tabu Search characteristics are incorporated into exploiting a Tabu-Search-based algorithm by combining them with the functional procedures of operation packing and releasing for improving the overall effectiveness. Several similar algorithms including K-means algorithm, Simulated Annealing algorithm, Tabu Search algorithm, and Tabu-Search-based algorithm are then tested with numerical examples to compare them one another. The test results show that the Tabu-Search-based algorithm outperforms the other algorithms.
Advisors
Sung, Chang-Supresearcher성창섭researcher
Description
한국과학기술원 : 산업공학과,
Publisher
한국과학기술원
Issue Date
1996
Identifier
105305/325007 / 000943541
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 산업공학과, 1996.2, [ ii, 56 p. ]

Keywords

Tabu Search; Clustering; 군집방안; 타부탐색기법

URI
http://hdl.handle.net/10203/41480
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=105305&flag=dissertation
Appears in Collection
IE-Theses_Master(석사논문)
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