Neural Network - An Application to the Food Production Data

Yuki Higuchi, Hiromasa Takeyasu, Yuta Tsuchida, Kazuhiro Takeyasu


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 food production data of prepared frozen foods. 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. We have obtained the good results.

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Business and Management Research
ISSN 1927-6001 (Print)   ISSN 1927-601X (Online)

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