Proceedings of the Fuzzy System Symposium
31st Fuzzy System Symposium
Session ID : WD2-3
Conference information

main
The Method to Improve Forecasting Accuracy by Using Neural Network - An Application to the Food Production Data
*Yuki HiguchiHiromasa TakeyasuYuta TsuchidaKazuhiro Takeyasu
Author information
CONFERENCE PROCEEDINGS FREE ACCESS

Details
Abstract
In industry, making a correct forecasting is inevitable. 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. There are some related researches made on this. However, it can be said that an application to sales forecasting is rather a few s a whole, 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.
Content from these authors
© 2015 Japan Society for Fuzzy Theory and Intelligent Informatics
Previous article Next article
feedback
Top