A Two-Stage Multi-Objective Genetic-Fuzzy Mining Algorithm
學年 101
學期 2
發表日期 2013-04-29
作品名稱 A Two-Stage Multi-Objective Genetic-Fuzzy Mining Algorithm
作品名稱（其他語言）
著者 Chun-Hao Chen Ji-Syuan He Tzung-Pei Hong
作品所屬單位 資訊工程學系暨研究所
出版者
會議名稱 2013 IEEE Symposium Series on Computational Intelligence
會議地點 Singapore
摘要 In this paper, we propose a two-stage multi-objective fuzzy mining algorithm for dealing with linguistic knowledge discovery. In the first stage, the multi-objective genetic lgorithm is used to derive a set of non-dominated membership functions (Pareto solutions) with two objective functions. In the second stage, the clustering technique is utilized to find representative solutions from the Pareto solutions. The epresentative solutions could be employed to mine fuzzy association rules according to the favorites of decision makers. Experiments on a simulation dataset are made and the results show the effectiveness of the proposed algorithm.
關鍵字 Multi-objective genetic algorithm, clustering technique, membership function, taxonomy, fuzzy association rule.
語言 en_US
收錄於 EI
會議性質 國際
校內研討會地點
研討會時間
通訊作者 Tzung-Pei Hong
國別
公開徵稿 Y
出版型式 電子版
出處 SSCI
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/88828 )

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