@article{851c18fb56e94022a3b96b5ca69a4245,
title = "Novel forecasting model based on improved wavelet transform, informative feature selection, and hybrid support vector machine on wind power forecasting",
abstract = "Wind speed/power prediction plays an important role in large-scale wind power penetration because of the wind volatility and uncertainty. In this paper, an accurate forecast model is presented based on improved wavelet transform, informative feature selection and hybrid forecast engine. The proposed forecasting engine is based on support vector machine which is an appropriate prediction forecast engine due to its ability to discover natural structures of wind speed/power variation. The mentioned forecast engine is equipped with an intelligent algorithm and enhances its prediction accuracy. For this purpose, we applied a new version of enhanced particle swarm optimization in this work as the optimization algorithm. Effectiveness of the proposed forecast model is extensively evaluated by real-world electricity market through comparison with well-known forecasting methods. Obtained numerical results and analysis demonstrate the validity and superiority of the proposed method.",
keywords = "E-PSO, Improved wavelet transform, Informative feature selection, ISVM, Wind power, n/a OA procedure",
author = "Zhenling Liu and Mahdi Hajiali and Amirhosein Torabi and Bahman Ahmadi and Rolando Simoes",
note = "Funding Information: This research was financially supported by Key Research Institute of Humanities and Social Science at Universities of Henan. The authors thanks to Emate(www.emate.ac.cn) for their excellent language service, as they had supplied translation and native proofreading from native speakers. Meanwhile, the revisions and suggestion on research method provided by IAMSET, an organizer in academic conferences service, are highly appreciated. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Funding Information: Acknowledgements This research was financially supported by Key Research Institute of Humanities and Social Science at Universities of Henan. The authors thanks to Emate(www.emate.ac.cn) for their excellent language service, as they had supplied translation and native proofreading from native speakers. Meanwhile, the revisions and suggestion on research method provided by IAMSET, an organizer in academic conferences service, are highly appreciated. Publisher Copyright: {\textcopyright} 2018, Springer-Verlag GmbH Germany, part of Springer Nature.",
year = "2018",
month = nov,
day = "1",
doi = "10.1007/s12652-018-0886-0",
language = "English",
volume = "9",
pages = "1919--1931",
journal = "Journal of ambient intelligence and humanized computing",
issn = "1868-5137",
publisher = "Springer",
number = "6",
}
