— Rapidly evolving businesses generate massive amounts of time-stamped data sequences and defy a demand for massively multivariate time series analysis. For such data the predict...
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 investigates cluster formation in decentralized sensor grids and focusses on predicting when the cluster formation converges to a stable configuration. The traffic volum...
—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...
In this paper, a Sequential Adaptive Fuzzy Inference System called SAFIS is developed based on the functional equivalence between a radial basis function network and a fuzzy infer...
Hai-Jun Rong, N. Sundararajan, Guang-Bin Huang, P....