Refereed full papers (journals, book chapters, international conferences)

1994

@article{HMO1994,
	vgclass =	{refpap},
	author =	{Tim Hill and Leorey Marquez and Marcus O'Connor and
	William Remus},
	title =	{Artificial neural network models for forecasting and
	decision making},
	journal =	{International Journal of Forecasting},
	volume =	{10},
	number =	{1},
	pages =	{5--15},
	month =	{June},
	year =	{1994},
	doi =	{http://dx.doi.org/10.1016/0169-2070(94)90045-0},
	url =	{http://212.67.202.199/~msewell/ann/HMOR93a.pdf},
	abstract =	{Some authors advocate artificial neural networks as a
	replacement for statistical forecasting and decision models; other
	authors are concerned that artificial neural networks might be oversold
	or just a fad. In this paper we review the literature comparing
	artificial neural networks and statistical models, particularly in
	regression-based forecasting, time series forecasting, and decision
	making. Our intention is to give a balanced assessment of the potential
	of artificial neural networks for forecasting and decision making
	models.

	We survey the literature and summarize several studies we have
	performed.  Overall, the empirical studies find artificial neural
	networks comparable with their statistical counterparts. We note the
	need to consider the many mathematical proofs underlying artificial
	neural networks to determine the best conditions for their use in
	forecasting and decision making.},
}