Time Series Forecasting with Neural Networks

		/vol02/cmxhk/	© Copyright 1995
		Volume 02	Received: Accepted:	---- ----

Time Series Forecasting with Neural Networks Feng Lin, Xing Huo Yu, Shirley Gregor and Richard Irons
Abstract
	A scheme for time series forecasting with a neural network is discussed in this paper. This scheme consists of three phases: detection of input patterns, determination of the number of neurons in hidden layer(s), and construction of a neural network forecaster. In the detection phase, autocorrelation analysis is used to identify input patterns of time series for training. Determination of the number of neurons in the hidden layer is done with Baum-Haussler rules. The calculated number of neurons for the hidden layers and the determined input patterns are then used to construct the neural network forecaster. Computer simulations are presented to show the effectiveness of the scheme.

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