Ensemble Nonlinear Autoregressive Exogenous Artificial Neural Networks for Short-Term Wind Speed and Power Forecasting

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Authors
  1. Men, Z.
  2. Yee, E.
  3. Lien, F-S.
  4. Yang, Z.
  5. Liu, Y.
Corporate Authors
Defence Research and Development Canada, Suffield Research Centre, Ralston AB (CAN);Waterloo CFD Engineering Consulting Inc., Waterloo ON (CAN);Waterloo Univ, Waterloo Ont (CAN) Dept of Mechanical and Mechatronics Engineering;SCHOOL OF RENEWABLE ENERGY, NORTH CHINA ELECTRIC POWER UNIVERSITY, BEIJING 102206 (CHINA)
Abstract
Keywords
artificial neural network;computational fluid dynamics;ensemble methodology;numerical weather prediction;particle swarm optimization;wind speed and power forecasting
Report Number
DRDC-RDDC-2014-P54 — External Literature
Date of publication
08 Sep 2014
Number of Pages
16
DSTKIM No
CA039523
CANDIS No
800448
Format(s):
Electronic Document(PDF)

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