In this paper we present a technique for prediction of electrical demand based on multiple models. The multiple models are composed by several local models, each one describing a r...
J. Jesus Rico Melgoza, Juan J. Flores, Constantino...
Application systems often need to react with certain actions whenever some preset conditions are satisfied. In many cases, the evaluation of these conditions takes long time, but...
— 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...
In this paper, the problem of time series prediction is studied. A Bayesian procedure based on Gaussian process models using a nonstationary covariance function is proposed. Exper...