scholarly journals Long-term forecasting of time series based on linear fuzzy information granules and fuzzy inference system

2017 ◽  
Vol 81 ◽  
pp. 1-27 ◽  
Author(s):  
Xiyang Yang ◽  
Fusheng Yu ◽  
Witold Pedrycz
2013 ◽  
Vol 385-386 ◽  
pp. 1411-1414 ◽  
Author(s):  
Xue Bo Jin ◽  
Jiang Feng Wang ◽  
Hui Yan Zhang ◽  
Li Hong Cao

This paper describes an architecture of ANFIS (adaptive network based fuzzy inference system), to the prediction of chaotic time series, where the goal is to minimize the prediction error. We consider the stock data as the time series. This paper focuses on how the stock data affect the prediction performance. In the experiments we changed the number of data as input of the ANFIS model, the type of membership functions and the desired goal error, thereby increasing the complexity of the training.


2020 ◽  
Vol 268 ◽  
pp. 114977 ◽  
Author(s):  
Mohammed Ali Jallal ◽  
Aurora González-Vidal ◽  
Antonio F. Skarmeta ◽  
Samira Chabaa ◽  
Abdelouhab Zeroual

Sign in / Sign up

Export Citation Format

Share Document