Paper presented in "Symposium on Signal and Information Processing for Optimizing Future Energy Systems" that was part of GlobalSip 2015 Conference.

Citation of the paper:

M. Alamaniotis, N. Bourbakis, and L.H. Tsoukalas, “Very-Short Term Forecasting of Electricity Price Signals Using a Pareto Composition of Kernel Machines in Smart Power Systems,” 3rd IEEE Global Conference on Signal and Information Processing, Orlando, FL, December 2015, pp. 1-5.

Authors:

M. Alamaniotis and L. H. Tsoukalas are with the Applied Intelligent Systems Laboratory, School of Nuclear Engineering, Purdue University, West Lafayette, IN 47907 USA

N. Bourbakis, is with the Computer Science and Engineering Department, Wright State University, Dayton, OH 45435 USA