Time series forecasting is one of the important problems in the time series analysis. As one of the most powerful analysis tools for time series forecasting, neural network (NN) has been receiving considerable attention since many years ago and a large number of improvements of NN-based forecasting on time series have appeared in the relevant literature. This paper reviews the structure improvement of NN and the main combination of NN and other pop technologies in the improvement of algorithms.


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    Title :

    A review of some main improved models for neural network forecasting on time series


    Contributors:
    Ming-liang Chai, (author) / Su Song, (author) / Ning-ning Li, (author)


    Publication date :

    2005-01-01


    Size :

    597408 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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