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This research investigates the use of ridge polynomial neural network (RPNN) as non-linear prediction model to forecast the future trends of financial time series. The network was used for the prediction of one step ahead and five steps ahead of two exchange rate signals; the British Pound to Euro and the Japanese Yen to British Pound. In order to deal with(More)
This paper presents a novel application of ridge polynomial neural network to forecast the future trends of financial time series data. The prediction capability of ridge polynomial neural network was tested on four different data sets; the US/EU exchange rate, the UK/EU exchange rate, the JP/EU exchange rate, and the IBM common stock closing price. The(More)
There has been some improvement in the treatment of preterm infants, which has helped to increase their chance of survival. However, the rate of premature births is still globally increasing. As a result, this group of infants are most at risk of developing severe medical conditions that can affect the respiratory, gastrointestinal, immune, central nervous,(More)
Motivated by the slow learning properties of multilayer perceptrons (MLPs) which utilize computa-tionally intensive training algorithms, such as the back-propagation learning algorithm, and can get trapped in local minima, this work deals with ridge polynomial neural networks (RPNN), which maintain fast learning properties and powerful mapping capabilities(More)