Abstract. In this paper, we investigate the application of adaptive ensemble models of Extreme Learning Machines (ELMs) to the problem of one-step ahead prediction in (non)stationa...
Mark van Heeswijk, Yoan Miche, Tiina Lindh-Knuutil...
: In this paper an approach for development of univariate time series prediction library in Java and its integration with an existing CLIPS related system is presented .A backpropa...
This paper presents a new method — the Time-delay Added Evolutionary Forecasting (TAEF) method — for time series prediction which performs an evolutionary search of the minimu...
Tiago A. E. Ferreira, Germano C. Vasconcelos, Paul...
In this paper, we review our work on a time series forecasting methodology based on the combination of unsupervised clustering and artificial neural networks. To address noise and...
Nicos G. Pavlidis, Vassilis P. Plagianakos, Dimitr...
Artificial Neural Networks are universal and highly flexible function approximators first used in the fields of cognitive science and engineering. In recent years, Neural Networks...