How effective are neural networks at forecasting and prediction? A review and evaluation

被引:7
作者
Adya, M [1 ]
Collopy, F
机构
[1] Univ Maryland Baltimore Cty, Dept Informat Syst, Baltimore, MD 21250 USA
[2] Case Western Reserve Univ, Cleveland, OH 44106 USA
关键词
artificial intelligence; machine learning; validation;
D O I
10.1002/(SICI)1099-131X(1998090)17:5/6<481::AID-FOR709>3.0.CO;2-Q
中图分类号
F [经济];
学科分类号
02 ;
摘要
Despite increasing applications of artificial neural networks (NNs) to forecasting over the past decade, opinions regarding their contribution are mixed. Evaluating research in this area has been difficult, due to lack of clear criteria. We identified eleven guidelines that could be used in evaluating this literature. Using these, we examined applications of NNs to business forecasting and prediction. We located 48 studies done between 1988 and 1994. For each, we evaluated how effectively the proposed technique was compared with alternatives (effectiveness of validation) and how well the technique was implemented (effectiveness of implementation). We found that eleven of the studies were both effectively validated and implemented. Another eleven studies were effectively validated and produced positive results, even though there were some problems with respect to the quality of their NN implementations. Of these 22 studies, 18 supported the potential of NNs for forecasting and prediction. (C) 1998 John Wiley & Sons, Ltd.
引用
收藏
页码:481 / 495
页数:15
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