Abstract. Some issues about the generalization of ANN training are investigated through experiments with several synthetic time series and real world time series. One commonly acce...
Wen Wang, Pieter H. A. J. M. van Gelder, J. K. Vri...
This paper presents an study about a new Hybrid method GRASPES - for time series prediction, inspired in F. Takens theorem and based on a multi-start metaheuristic for combinatori...
Aranildo Rodrigues Lima Junior, Tiago Alessandro E...
—This paper presents the advances of a research using a combination of recurrent and feed-forward neural networks for long term prediction of chaotic time series. It is known tha...
Abstract. An application of the recently proposed generalized relevance learning vector quantization (GRLVQ) to the analysis and modeling of time series data is presented. We use G...
— We consider the regression problem for financial time series. Typically, financial time series are non-stationary and volatile in nature. Because of its good generalization p...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...