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...
One of the most important challenges for the researchers in the 21st Century is related to global heating and climate change that can have as consequence the intensiļ¬cation of na...
Luciana A. S. Romani, Ana Maria Heuminski de &Aacu...
This article proposes knowledge-based short-time prediction methods for multivariate streaming time series, relying on the early recognition of local patterns. A parametric, well-i...
In many applications that track and analyze spatiotemporal data, movements obey periodic patterns; the objects follow the same routes (approximately) over regular time intervals. ...
Nikos Mamoulis, Huiping Cao, George Kollios, Mario...
Theproblemof efficiently and accurately locating patterns of interest in massivetimeseries data sets is an important and non-trivial problemin a wide variety of applications, incl...