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High Technology Letters - Abstract Contents
2  Time:  2017-6-20
Incremental learning of the triangular membership functions based on singleª²pass FCM and CHC genetic model
Huo Weigang (»ôγ¸Ù), Qu Feng, Zhang Yuxiang
Get Time£º2017-3-31 14:11:18  Publishing Time£º2017-3-31 14:11:18
In order to improve the efficiency of learning the triangular membership functions (TMFs) for mining fuzzy association rule (FAR) in dynamic database, a singleª²pass fuzzy c means (SPFCM) algorithm is combined with the realª²coded 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.
Key words: incremental learning, triangular membership function (TMFs), fuzzy association rule (FAR), realª²coded CHC
2017-3-31 14:11:18 [Abstract] [PDF]

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