Wind speed forecasting approach using secondary decomposition algorithm and Elman neural networks-Reference-Cited by-同舟云学术

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Wind speed forecasting approach using secondary decomposition algorithm and Elman neural networks

Published:2015-11 Issue: Volume:157 Page:183-194
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Liu Hui,Tian Hong-qi,Liang Xi-feng,Li Yan-fei

Funder

National Natural Science Foundation of China

Scientific Research Fund of Hunan Provincial Education Department

Shenghua Yu-ying Talents Program of the Central South University

Fundamental Research Funds for the Central Universities of China

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference34 articles.

1. A hybrid statistical method to predict wind speed and wind power;Liu;Renew Energy,2010

2. A new approach to very short term wind speed prediction using k-nearest neighbor classification;Yesilbudak;Energy Convers Manage,2013

3. Soman SS, Zareipour H, Malik O, Mandal P. A review of wind power and wind speed forecasting methods with different time horizons. In: North American Power Symposium (NAPS), 2010. p. 1–8.

4. A review on the forecasting of wind speed and generated power;Lei;Renew Sustain Energy Rev,2009

5. Day-ahead wind speed forecasting using f-ARIMA models;Kavasseri;Renew Energy,2009

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