A novel competitive swarm optimized RBF neural network model for short-term solar power generation forecasting-Reference-Cited by-同舟云学术

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A novel competitive swarm optimized RBF neural network model for short-term solar power generation forecasting

Published:2020-07 Issue: Volume:397 Page:415-421
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Yang Zhile^ORCID,Mourshed Monjur^ORCID,Liu Kailong^ORCID,Xu Xinzhi,Feng Shengzhong

Funder

European Commission

NSFC

Natural Science Foundation of Guangdong Province

SIAT, CAS

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference42 articles.

1. The 2015 paris climate change conference: Cop21;Rhodes;Sci Prog,2016

2. Distributed optimization for multiagent systems: An edge-based fixed-time consensus approach;Ning;IEEE transactions on cybernetics,2017

3. IRENA, Renewable capacity statistics 2019, International Renewable Energy Agency, 2019.

4. Solar forecasting methods for renewable energy integration;Inman;Progress in energy and combustion science,2013

5. Review of photovoltaic power forecasting;Antonanzas;Solar Energy,2016

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