This paper presents a method that combines Mutual Information and k-Nearest Neighbors approximator for time series prediction. Mutual Information is used for input selection. K-Nea...
Abstract— This paper proposes a combination of methodologies based on a recent development –called Extreme Learning Machine (ELM)– decreasing drastically the training time of...
Antti Sorjamaa, Yoan Miche, Robert Weiss, Amaury L...
This paper describes our work in learning online models that forecast real-valued variables in a high-dimensional space. A 3GB database was collected by sampling 421 real-valued s...
— This paper suggests a constructive fuzzy system modeling for time series prediction. The model proposed is based on Takagi-Sugeno system and it comprises two phases. First, a f...
Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...