Forecasting with artificial neural networks:

Guoqiang Zhang, B. Eddy Patuwo, Michael Y. Hu
<span title="">1998</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/mcmshkvfz5fgjnpsxca5gv35he" style="color: black;">International Journal of Forecasting</a> </i> &nbsp;
Interest in using artificial neural networks (ANNs) for forecasting has led to a tremendous surge in research activities in the past decade. While ANNs provide a great deal of promise, they also embody much uncertainty. Researchers to date are still not certain about the effect of key factors on forecasting performance of ANNs. This paper presents a state-of-the-art survey of ANN applications in forecasting. Our purpose is to provide (1) a synthesis of published research in this area, (2)
more &raquo; ... ts on ANN modeling issues, and (3) the future research directions.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/s0169-2070(97)00044-7">doi:10.1016/s0169-2070(97)00044-7</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mh7hd4qvnjar7mkdvy63d2if5y">fatcat:mh7hd4qvnjar7mkdvy63d2if5y</a> </span>
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