In industry, making a correct forecasting is a very important matter. If the correct forecasting is not executed, there arise a lot of stocks and/or it also causes lack of goods. Time series analysis, neural networks and other methods are applied to this problem. In this paper, neural network is applied and Multilayer perceptron Algorithm is newly developed. The method is applied to the production data of Udon Noodles. When there is a big change of the data, the neural networks cannot learn the past data properly, therefore we have devised a new method to cope with this. Repeating the data into plural section, smooth change is established and we could make a neural network learn more smoothly. Thus, we have obtained good results. The result is compared with the method we have developed before as well as ARIMA model. We have obtained the good results.
Mathematics Subject Classification: 91B70
Keywords: forecasting, neural network, time series analysis, ARIMA model
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