首页> 外文会议>International work-conference on artificial neural networks;IWANN 2011 >Forecasting Based on Short Time Series Using ANNs and Grey Theory - Some Basic Comparisons
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Forecasting Based on Short Time Series Using ANNs and Grey Theory - Some Basic Comparisons

机译:基于ANN和灰色理论的短时间序列预测-一些基本比较。

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摘要

Two modern forecasting methods based on short time series are compared. Results obtained by use of artificial neural nets (ANNs), are contrasted to the ones produced by use of the so called grey theory or Grey Model (GM). Specifically, the Feed-Forward Accommodated for Prediction (FFAP) and the Time Controlled Recurrent (TCR) ANNs are used along with the GM(1,1) algorithm for one- and two-steps-ahead forecasting of various quantities (electricity loads, number of fixed telephones lines, obsolete computers, etc). Advantages of the ANN concept are observed.
机译:比较了两种基于短时间序列的现代预测方法。使用人工神经网络(ANN)获得的结果与使用所谓的灰色理论或灰色模型(GM)产生的结果形成对比。具体来说,前馈适应预测(FFAP)和时间控制循环(TCR)人工神经网络与GM(1,1)算法一起用于各种数量(电力负荷,固定电话线,陈旧的计算机等的数量)。可以看到ANN概念的优点。

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