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NSYSU

1. Song, Huei-jyun. A Hyper-Heuristic Clustering Algorithm.

Degree: Master, Computer Science and Engineering, 2012, NSYSU

The so-called heuristics have been widely used in solving combinatorial optimization problems because they provide a simple but effective way to find an approximate solution. These technologies are very useful for users who do not need the exact solution but who care very much about the response time. For every existing heuristic algorithm has its pros and cons, a hyper-heuristic clustering algorithm based on the diversity detection and improvement detection operators to determine when to switch from one heuristic algorithm to another is presented to improve the clustering result in this paper. Several well-known datasets are employed to evaluate the performance of the proposed algorithm. Simulation results show that the proposed algorithm can provide a better clustering result than the state-of-the-art heuristic algorithms compared in this paper, namely, k-means, simulated annealing, tabu search, and genetic k-means algorithm. Advisors/Committee Members: Shiann-rong Kuang (chair), Chun-wei Tsai (chair), Ming-chao Chiang (committee member), Chu-sing Yang (chair).

Subjects/Keywords: diversified detection; metaheuristics algorithm; clustering problem; Hyper-heuristic algorithm

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Song, H. (2012). A Hyper-Heuristic Clustering Algorithm. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0907112-211759

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Song, Huei-jyun. “A Hyper-Heuristic Clustering Algorithm.” 2012. Thesis, NSYSU. Accessed April 10, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0907112-211759.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Song, Huei-jyun. “A Hyper-Heuristic Clustering Algorithm.” 2012. Web. 10 Apr 2020.

Vancouver:

Song H. A Hyper-Heuristic Clustering Algorithm. [Internet] [Thesis]. NSYSU; 2012. [cited 2020 Apr 10]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0907112-211759.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Song H. A Hyper-Heuristic Clustering Algorithm. [Thesis]. NSYSU; 2012. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0907112-211759

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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