Article révisé par les pairs
Résumé : This paper proposes a multiple kernel regression (MKr) to predict water demand in the presence of a continuous source of information. MKr extends the simple support vector regression (SVR) to a combination of kernels from as many distinct types as kinds of input data are available. In addition, two on-line learning methods to obtain real time predictions as new data arrives to the system are tested by a real-world case study. The accuracy and computational efficiency of the results indicate that our proposal is a suitable tool for making adequate management decisions in the smart cities environment © 2013 The Authors.