DYNAMIC APERIODIC NEURAL NETWORK FOR TIME SERIES PREDICTION

Chiu-Che Tseng ()
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Chiu-Che Tseng: Department of Computer Science and Information Systems Texas A&M University-Commerce

Portuguese Journal of Management Studies, 2007, vol. XII, issue 2, 99-113

Abstract: There are many things that humans find easy to do that computers are currently unable to do. Tasks such as visual pattern manipulating objects by touch, and navigating in a complex world are easy for humans. Yet, despite decades of research, we have no viable algorithms for performing these and other cognitive functions on a computer. In this study, we used a bio-inspired neural network called a KAset neural network to perform a time series predictive task. The results from our experiments showed that the predictive accuracy with this method was better in most markets than results obtained using a random walk method.

Keywords: Kset neural network; Time series; Prediction (search for similar items in EconPapers)
Date: 2007
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Persistent link: https://EconPapers.repec.org/RePEc:pjm:journl:v:xii:y:2007:i:2:p:99-113

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