Machine Learning Applications in Renewable Energy (MLARE) Research: A Publication Trend and Bibliometric Analysis Study (2012–2021)
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- Helbing, Georg & Ritter, Matthias, 2018. "Deep Learning for fault detection in wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 189-198.
- Ahmad, Tanveer & Chen, Huanxin, 2019. "Deep learning for multi-scale smart energy forecasting," Energy, Elsevier, vol. 175(C), pages 98-112.
- Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Costa, 2018. "The effect of multidisciplinary collaborations on research diversification," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 423-433, July.
- Jungwon Yu & June Ho Park & Sungshin Kim, 2018. "A New Input Selection Algorithm Using the Group Method of Data Handling and Bootstrap Method for Support Vector Regression Based Hourly Load Forecasting," Energies, MDPI, vol. 11(11), pages 1-20, October.
- Davies, Benjamin & Gush, Jason & Hendy, Shaun C. & Jaffe, Adam B., 2022.
"Research funding and collaboration,"
Research Policy, Elsevier, vol. 51(2).
- Benjamin Davies & Jason Gush & Shaun C. Hendy & Adam B. Jaffe, 2020. "Research Funding and Collaboration," NBER Working Papers 27916, National Bureau of Economic Research, Inc.
- Benjamin Davies & Jason Gush & Shaun C. Hendy & Adam B. Jaffe, 2020. "Research Funding and Collaboration," Working Papers 20_12, Motu Economic and Public Policy Research.
- Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Costa, 2017. "Do interdisciplinary research teams deliver higher gains to science?," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 317-336, April.
- Sinsel, Simon R. & Riemke, Rhea L. & Hoffmann, Volker H., 2020. "Challenges and solution technologies for the integration of variable renewable energy sources—a review," Renewable Energy, Elsevier, vol. 145(C), pages 2271-2285.
- Ashiwani Yadav & Nitai Pal & Jagannath Patra & Monika Yadav, 2020. "Strategic planning and challenges to the deployment of renewable energy technologies in the world scenario: its impact on global sustainable development," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(1), pages 297-315, January.
- Adams, James D. & Black, Grant C. & Clemmons, J. Roger & Stephan, Paula E., 2005.
"Scientific teams and institutional collaborations: Evidence from U.S. universities, 1981-1999,"
Research Policy, Elsevier, vol. 34(3), pages 259-285, April.
- James D. Adams, 2004. "Scientific Teams and Institution Collaborations: Evidence from U.S. Universities, 1981-1999," NBER Working Papers 10640, National Bureau of Economic Research, Inc.
- Hua, Haochen & Qin, Yuchao & Hao, Chuantong & Cao, Junwei, 2019. "Optimal energy management strategies for energy Internet via deep reinforcement learning approach," Applied Energy, Elsevier, vol. 239(C), pages 598-609.
- Marek Kwiek, 2020. "Internationalists and locals: international research collaboration in a resource-poor system," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 57-105, July.
- Li, Liang & Yuan, Zhiming & Gao, Yan, 2018. "Maximization of energy absorption for a wave energy converter using the deep machine learning," Energy, Elsevier, vol. 165(PA), pages 340-349.
- del Río, Pablo & Unruh, Gregory, 2007. "Overcoming the lock-out of renewable energy technologies in Spain: The cases of wind and solar electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(7), pages 1498-1513, September.
- Paul Lehmann & Felix Creutzig & Melf-Hinrich Ehlers & Nele Friedrichsen & Clemens Heuson & Lion Hirth & Robert Pietzcker, 2012. "Carbon Lock-Out: Advancing Renewable Energy Policy in Europe," Energies, MDPI, vol. 5(2), pages 1-32, February.
- Bedi, Jatin & Toshniwal, Durga, 2019. "Deep learning framework to forecast electricity demand," Applied Energy, Elsevier, vol. 238(C), pages 1312-1326.
- Johari, Anwar & Nyakuma, Bemgba Bevan & Mohd Nor, Shadiah Husna & Mat, Ramli & Hashim, Haslenda & Ahmad, Arshad & Yamani Zakaria, Zaki & Tuan Abdullah, Tuan Amran, 2015. "The challenges and prospects of palm oil based biodiesel in Malaysia," Energy, Elsevier, vol. 81(C), pages 255-261.
- Cosimo Magazzino & Marco Mele & Giovanna Morelli, 2021. "The Relationship between Renewable Energy and Economic Growth in a Time of Covid-19: A Machine Learning Experiment on the Brazilian Economy," Sustainability, MDPI, vol. 13(3), pages 1-22, January.
- Ma, Ting & Guo, Zhixiong & Lin, Mei & Wang, Qiuwang, 2021. "Recent trends on nanofluid heat transfer machine learning research applied to renewable energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
- Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Di Costa, 2019. "The collaboration behavior of top scientists," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(1), pages 215-232, January.
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Cited by:
- Abdelhamid Zaidi & Samuel-Soma M. Ajibade & Majd Musa & Festus Victor Bekun, 2023. "New Insights into the Research Landscape on the Application of Artificial Intelligence in Sustainable Smart Cities: A Bibliometric Mapping and Network Analysis Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 13(4), pages 287-299, July.
- Samuel-Soma Ajibade & Abdelhamid Zaidi & Asamh Saleh M. Al Luhayb & Anthonia Oluwatosin Adediran & Liton Chandra Voumik & Fazle Rabbi, 2023. "New Insights into the Emerging Trends Research of Machine and Deep Learning Applications in Energy Storage: A Bibliometric Analysis and Publication Trends," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 303-314, September.
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Keywords
machine learning; algorithms; supervised learning; unsupervised learning; deep learning; renewable energy; forecasting; optimization;All these keywords.
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