Proceedings of the Fuzzy System Symposium
29th Fuzzy System Symposium
Session ID : MC2-2
Conference information

main
The Method to improve Forecasting Accuracy by Using Multilayer perceptron Algorithm -An Application to the Airlines Passengers and Cargo Data
Yuta TsuchidaTatsuhiro Kuroda*Kazuhiro TakeyasuMichifumu Yoshioka
Author information
CONFERENCE PROCEEDINGS FREE ACCESS

Details
Abstract
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 Airlines Passengers and Cargo Data. 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.
Content from these authors
© 2013 Japan Society for Fuzzy Theory and Intelligent Informatics
Previous article Next article
feedback
Top