Smart Grid Project Benefit Evaluation Based on a Hybrid Intelligent Model
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- Yi Liang & Haichao Wang, 2021. "Using Improved SPA and ICS-LSSVM for Sustainability Assessment of PV Industry along the Belt and Road," Energies, MDPI, vol. 14(12), pages 1-19, June.
- Guoqing An & Ziyao Jiang & Libo Chen & Xin Cao & Zheng Li & Yuyang Zhao & Hexu Sun, 2021. "Ultra Short-Term Wind Power Forecasting Based on Sparrow Search Algorithm Optimization Deep Extreme Learning Machine," Sustainability, MDPI, vol. 13(18), pages 1-18, September.
- Bemani, Amin & Xiong, Qingang & Baghban, Alireza & Habibzadeh, Sajjad & Mohammadi, Amir H. & Doranehgard, Mohammad Hossein, 2020. "Modeling of cetane number of biodiesel from fatty acid methyl ester (FAME) information using GA-, PSO-, and HGAPSO- LSSVM models," Renewable Energy, Elsevier, vol. 150(C), pages 924-934.
- Wu, Yunna & Zhang, Ting, 2021. "Risk assessment of offshore wave-wind-solar-compressed air energy storage power plant through fuzzy comprehensive evaluation model," Energy, Elsevier, vol. 223(C).
- Liang, Yi & Niu, Dongxiao & Hong, Wei-Chiang, 2019. "Short term load forecasting based on feature extraction and improved general regression neural network model," Energy, Elsevier, vol. 166(C), pages 653-663.
- Spiros Livieratos & Vasiliki-Emmanouela Vogiatzaki & Panayotis G. Cottis, 2013. "A Generic Framework for the Evaluation of the Benefits Expected from the Smart Grid," Energies, MDPI, vol. 6(2), pages 1-21, February.
- Chengtian Ouyang & Donglin Zhu & Yaxian Qiu, 2021. "Lens Learning Sparrow Search Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-17, May.
- Haichao Wang & Yi Liang & Wei Ding & Dongxiao Niu & Si Li & Fenghua Wang, 2020. "The Improved Least Square Support Vector Machine Based on Wolf Pack Algorithm and Data Inconsistency Rate for Cost Prediction of Substation Projects," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-14, December.
- Hafeez, Ghulam & Khan, Imran & Jan, Sadaqat & Shah, Ibrar Ali & Khan, Farrukh Aslam & Derhab, Abdelouahid, 2021. "A novel hybrid load forecasting framework with intelligent feature engineering and optimization algorithm in smart grid," Applied Energy, Elsevier, vol. 299(C).
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Keywords
smart city; smart grid; benefit evaluation; improved TOPSIS; MSSA; LSTM;All these keywords.
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