Comparison of echo state network and feed-forward neural networks in electrical load forecasting for demand response programs-Reference-Cited by-同舟云学术

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Comparison of echo state network and feed-forward neural networks in electrical load forecasting for demand response programs

Published:2021-06 Issue: Volume:184 Page:282-293
ISSN:0378-4754
Container-title:Mathematics and Computers in Simulation
language:en
Short-container-title:Mathematics and Computers in Simulation

Author:

Mansoor Muhammad,Grimaccia Francesco,Leva Sonia,Mussetta Marco

Publisher

Elsevier BV

Subject

Applied Mathematics,Modeling and Simulation,Numerical Analysis,General Computer Science,Theoretical Computer Science

Reference33 articles.

1. DROpS: A demand response optimization scheme in SDN-enabled smart energy ecosystem;Aujla;Inform. Sci.,2019

2. Energy management optimization of a smart wind power plant comparing heuristic and linear programming methods;Bourbon;Math. Comput. Simulation,2019

3. Time Series Analysis: Forecasting and Control;Box,2015

4. A Dendrite method for cluster analysis;Calinski;Commun. Stat.-Theory Methods,1974

5. Load/price forecasting and managing demand response for smart grids: Methodologies and challenges;Chan;IEEE Signal Process. Mag.,2012

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