Long-Term Forecasting of Time Series Based on Sliding Window Information Granules and Fuzzy Inference System

2018 ◽  
Author(s):  
Wei Zhou ◽  
Degang Wang ◽  
Hongxing Li ◽  
Wenyan Song
Keyword(s):  
Time Series ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Sliding Window ◽  
Inference System ◽  
Information Granules ◽  
Long Term Forecasting

ANFIS Model for Time Series Prediction

2013 ◽  
Vol 385-386 ◽  
pp. 1411-1414 ◽  
Author(s):  
Xue Bo Jin ◽  
Jiang Feng Wang ◽  
Hui Yan Zhang ◽  
Li Hong Cao
Keyword(s):  
Time Series ◽  
Fuzzy Inference System ◽  
Prediction Error ◽  
Fuzzy Inference ◽  
Time Series Prediction ◽  
Prediction Performance ◽  
Membership Functions ◽  
Adaptive Network ◽  
Anfis Model ◽  
Inference System

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.

A hybrid neuro-fuzzy inference system-based algorithm for time series forecasting applied to energy consumption prediction

2020 ◽  
Vol 268 ◽  
pp. 114977 ◽  
Author(s):  
Mohammed Ali Jallal ◽  
Aurora González-Vidal ◽  
Antonio F. Skarmeta ◽  
Samira Chabaa ◽  
Abdelouhab Zeroual
Keyword(s):  
Time Series ◽  
Energy Consumption ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Time Series Forecasting ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Energy Consumption Prediction ◽  
Consumption Prediction
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