The Box-Jenkins analysis and neural networks: prediction and time series modelling

被引:49
作者
BuHamra, S
Smaoui, N
Gabr, M
机构
[1] Kuwait Univ, Dept Math & Comp Sci, Kuwait 13060, Kuwait
[2] Kuwait Univ, Dept Stat & Operat Res, Kuwait 13060, Kuwait
关键词
Box-Jenkins analysis; autoregressive integrated moving average model; artificial neural networks; time series modelling;
D O I
10.1016/S0307-904X(03)00079-9
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Two approaches, namely the Box-Jenkins (BJ) approach and the artificial neural networks (ANN) approach were combined to model time series data of water consumption in Kuwait. The BJ approach was used to predict unrecorded water consumption data from May 1990 to December 1991 due to the Iraqi invasion of Kuwait in August 1990. A supervised feedforward back-propagation neural network was then designed, trained and tested to model and predict water consumption from January 1980 to December 1999. It is interesting to note that the lagged or delayed variables obtained from the BJ approach and used in neural networks provide a better ANN model than the one obtained either blindly in blackbox mode as has been suggested or from traditional known methods. (C) 2003 Elsevier Inc. All rights reserved.
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页码:805 / 815
页数:11
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