This paper presents a new approach for time series prediction using local dynamic modeling. The proposed method is composed of three blocks: a Time Delay Line that transforms the o...
Recurrent Self-Organizing Map (RSOM) is studied in three di erent time series prediction cases. RSOM is used to cluster the series into local data sets, for which corresponding lo...
Timo Koskela, Markus Varsta, Jukka Heikkonen, Kimm...
Background: The central role of transcription factors (TFs) in higher eukaryotes has led to much interest in deciphering transcriptional regulatory interactions. Even in the best ...
Henning Redestig, Daniel Weicht, Joachim Selbig, M...
Most financial time series processes are nonstationary and their frequency characteristics are time-dependant. In this paper we present a time series summarization and prediction ...
Abstract— This paper presents a novel support vector regression (SVR) network for financial time series prediction. The SVR network consists of two layers of SVR: transformation...