To improve the intelligence of engineering vehicle shift decisions, a kind of adaptive neuro-fuzzy inference system (ANFIS) is proposed. A test simulation based on the data that are obtained from a shift experiment on a ZL50E loader transmission system, is also developed. The simulation results show that this shift-decision system can make correct gear-box shift decisions according to the operational situation. This system is an effective method for making shift decisions. It overcomes the shortcoming of fuzzy inference, which doesn't have a learning function, and the weakness of neural networks which cannot express fuzzy language.


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    Title :

    An adaptive neuro-fuzzy inference system for engineering-vehicle shift decisions


    Contributors:
    Wang Zhuo (author) / Zhao, Dingxuan (author)

    Published in:

    Heavy Vehicle Systems ; 9 , 4 ; 354-365


    Publication date :

    2002


    Size :

    12 Seiten, 4 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




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