| Huo Weigang (霍纬纲),Qu Feng,Zhang Yuxiang.[J].高技术通讯(英文),2017,23(1):7~15 |
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| Incremental learning of the triangular membership functions based on single-pass FCM and CHC genetic model |
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| DOI：10.3772/j.issn.1006-6748.2017.01.002 |
| 中文关键词: |
| 英文关键词: incremental learning, triangular membership function (TMFs), fuzzy association rule (FAR), real-coded CHC |
| 基金项目: |
| Author Name | Affiliation | | Huo Weigang (霍纬纲) | | | Qu Feng | | | Zhang Yuxiang | |
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| 中文摘要: |
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| 英文摘要: |
| In order to improve the efficiency of learning the triangular membership functions (TMFs) for mining fuzzy association rule (FAR) in dynamic database, a single-pass fuzzy c means (SPFCM) algorithm is combined with the real-coded CHC genetic model to incrementally learn the TMFs. The cluster centers resulting from SPFCM are regarded as the midpoint of TMFs. The population of CHC is generated randomly according to the cluster center and constraint conditions among TMFs. Then a new population for incremental learning is composed of the excellent chromosomes stored in the first genetic process and the chromosomes generated based on the cluster center adjusted by SPFCM. The experiments on real datasets show that the number of generations converging to the solution of the proposed approach is less than that of the existing batch learning approach. The quality of TMFs generated by the approach is comparable to that of the batch learning approach. Compared with the existing incremental learning strategy, the proposed approach is superior in terms of the quality of TMFs and time cost. |
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