Abstract
Recently, Kimura et al. proposed a demand forecasting model for the purpose of predicting the demand of a directly succeeding period based on the past demand series using layered neural networks. In this paper, as an extension of their model, we consider a demand forecasting model for the purpose of predicting simultaneously the demands of several succeeding periods. Then, we propose a predicting method via layered neural networks based on differences of demands instead of demands in their model. Moreover, the effect of using the variable slope method, which the synaptic interconnection strength and the characteristic function of units are simultaneously renewed, is also investigated.
