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Very-Short Term Forecasting of Electricity Price Signals Using a Pareto Composition of Kernel Machines in Smart Power Systems

Abstract: 

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

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Paper Details

Authors:
Nikolaos Bourbakis, Lefteri H. Tsoukalas
Submitted On:
23 February 2016 - 1:44pm
Short Link:
Type:
Presentation Slides
Event:
Presenter's Name:
Miltiadis (Miltos) Alamaniotis
Document Year:
2015
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Document Files

GlobalSip_2015_MA.pdf

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[1] Nikolaos Bourbakis, Lefteri H. Tsoukalas, "Very-Short Term Forecasting of Electricity Price Signals Using a Pareto Composition of Kernel Machines in Smart Power Systems", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/483. Accessed: Jul. 05, 2020.
@article{483-15,
url = {http://sigport.org/483},
author = {Nikolaos Bourbakis; Lefteri H. Tsoukalas },
publisher = {IEEE SigPort},
title = {Very-Short Term Forecasting of Electricity Price Signals Using a Pareto Composition of Kernel Machines in Smart Power Systems},
year = {2015} }
TY - EJOUR
T1 - Very-Short Term Forecasting of Electricity Price Signals Using a Pareto Composition of Kernel Machines in Smart Power Systems
AU - Nikolaos Bourbakis; Lefteri H. Tsoukalas
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/483
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Nikolaos Bourbakis, Lefteri H. Tsoukalas. (2015). Very-Short Term Forecasting of Electricity Price Signals Using a Pareto Composition of Kernel Machines in Smart Power Systems. IEEE SigPort. http://sigport.org/483
Nikolaos Bourbakis, Lefteri H. Tsoukalas, 2015. Very-Short Term Forecasting of Electricity Price Signals Using a Pareto Composition of Kernel Machines in Smart Power Systems. Available at: http://sigport.org/483.
Nikolaos Bourbakis, Lefteri H. Tsoukalas. (2015). "Very-Short Term Forecasting of Electricity Price Signals Using a Pareto Composition of Kernel Machines in Smart Power Systems." Web.
1. Nikolaos Bourbakis, Lefteri H. Tsoukalas. Very-Short Term Forecasting of Electricity Price Signals Using a Pareto Composition of Kernel Machines in Smart Power Systems [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/483