Many time series prediction methods have focused on single step or short term prediction problems due to the inherent difficulty in controlling the propagation of errors from one ...
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...
Abstract. Rainfall in Kerala State, the southern part of Indian Peninsula in particular is caused by the two monsoons and the two cyclones every year. In general, climate and rainf...
Motivated by a broad range of potential applications, we address the quantile prediction problem of real-valued time series. We present a sequential quantile forecasting model bas...
Prediction of financial time series using artificial neural networks has been the subject of many publications, even if the predictability of financial series remains a subject of ...
Amaury Lendasse, John Aldo Lee, Eric de Bodt, Vinc...