Selviah, D.R. and Shawash, J. (2009) Generalized correlation higher order neural networks for financial time series prediction. In: Zhang, M., (ed.) Artificial Higher Order Neural Networks for Economics and Business. (pp. 212-249). IGI/ Information Science Reference: Hershey, US.
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Book description: Artificial Higher Order Neural Networks (HONNs) significantly change the research methodology that is used in economics and business areas for nonlinear data simulation and prediction. With the important advances in HONNs, it becomes imperative to remain knowledgeable about its benefits and improvements. Artificial Higher Order Neural Networks for Economics and Business is the first book to provide practical education and applications for the millions of professionals working in economics, accounting, finance and other business areas on HONNs and the ease of their usage to obtain more accurate application results. This source provides significant, informative advancements in the subject and introduces the concepts of HONN group models and adaptive HONNs.
|Title:||Generalized correlation higher order neural networks for financial time series prediction|
|UCL classification:||UCL > School of BEAMS > Faculty of Engineering Science > Electronic and Electrical Engineering|
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