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Multifactor-influenced energy consumption forecasting using enhanced back-propagation neural network

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Cited by:

  1. Mohsen Sadegh Amalnick & Naser Habibifar & Mahdi Hamid & Mahdi Bastan, 2020. "An intelligent algorithm for final product demand forecasting in pharmaceutical units," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(2), pages 481-493, April.
  2. Bilgili, Mehmet & Pinar, Engin, 2023. "Gross electricity consumption forecasting using LSTM and SARIMA approaches: A case study of Türkiye," Energy, Elsevier, vol. 284(C).
  3. He, Yan & Wu, Pengcheng & Li, Yufeng & Wang, Yulin & Tao, Fei & Wang, Yan, 2020. "A generic energy prediction model of machine tools using deep learning algorithms," Applied Energy, Elsevier, vol. 275(C).
  4. Teklebrhan Negash & Erik Möllerström & Fredric Ottermo, 2020. "An Assessment of Wind Energy Potential for the Three Topographic Regions of Eritrea," Energies, MDPI, vol. 13(7), pages 1-12, April.
  5. David Puga-Gil & Gonzalo Astray & Enrique Barreiro & Juan F. Gálvez & Juan Carlos Mejuto, 2022. "Global Solar Irradiation Modelling and Prediction Using Machine Learning Models for Their Potential Use in Renewable Energy Applications," Mathematics, MDPI, vol. 10(24), pages 1-21, December.
  6. Lai, Changzhi & Wang, Yu & Fan, Kai & Cai, Qilin & Ye, Qing & Pang, Haoqiang & Wu, Xi, 2022. "An improved forecasting model of short-term electric load of papermaking enterprises for production line optimization," Energy, Elsevier, vol. 245(C).
  7. Karakurt, Izzet, 2021. "Modelling and forecasting the oil consumptions of the BRICS-T countries," Energy, Elsevier, vol. 220(C).
  8. Yi Xiao & Keying Li & Yi Hu & Jin Xiao & Shouyang Wang, 2020. "Combining STRIPAT model and gated recurrent unit for forecasting nature gas consumption of China," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(7), pages 1325-1343, October.
  9. Wang, Lining & Mao, Mingxuan & Xie, Jili & Liao, Zheng & Zhang, Hao & Li, Huanxin, 2023. "Accurate solar PV power prediction interval method based on frequency-domain decomposition and LSTM model," Energy, Elsevier, vol. 262(PB).
  10. Hu, Huanling & Wang, Lin & Lv, Sheng-Xiang, 2020. "Forecasting energy consumption and wind power generation using deep echo state network," Renewable Energy, Elsevier, vol. 154(C), pages 598-613.
  11. Marcin Rabe & Dalia Streimikiene & Yuriy Bilan, 2020. "Model of Optimization of Wind Energy Production in the Light of Legal Changes in Poland," Energies, MDPI, vol. 13(7), pages 1-15, March.
  12. Feng, Qianqian & Sun, Xiaolei & Hao, Jun & Li, Jianping, 2021. "Predictability dynamics of multifactor-influenced installed capacity: A perspective of country clustering," Energy, Elsevier, vol. 214(C).
  13. Peng, Lu & Wang, Lin & Xia, De & Gao, Qinglu, 2022. "Effective energy consumption forecasting using empirical wavelet transform and long short-term memory," Energy, Elsevier, vol. 238(PB).
  14. Zhou, Cheng & Chen, Xiyang, 2019. "Predicting energy consumption: A multiple decomposition-ensemble approach," Energy, Elsevier, vol. 189(C).
  15. He, Yan-Lin & Wang, Ping-Jiang & Zhang, Ming-Qing & Zhu, Qun-Xiong & Xu, Yuan, 2018. "A novel and effective nonlinear interpolation virtual sample generation method for enhancing energy prediction and analysis on small data problem: A case study of Ethylene industry," Energy, Elsevier, vol. 147(C), pages 418-427.
  16. Liu, Bingchun & Song, Chengyuan & Wang, Qingshan & Zhang, Xinming & Chen, Jiali, 2022. "Research on regional differences of China's new energy vehicles promotion policies: A perspective of sales volume forecasting," Energy, Elsevier, vol. 248(C).
  17. Hu, Huanling & Wang, Lin & Peng, Lu & Zeng, Yu-Rong, 2020. "Effective energy consumption forecasting using enhanced bagged echo state network," Energy, Elsevier, vol. 193(C).
  18. Linlin Zhao & Zhansheng Liu & Jasper Mbachu, 2019. "Energy Management through Cost Forecasting for Residential Buildings in New Zealand," Energies, MDPI, vol. 12(15), pages 1-24, July.
  19. Hadi Sasana & Achma Hendra Setiawan & Fitri Ariyanti & Imam Ghozali, 2017. "The Effect of Energy Subsidy on the Environmental Quality in Indonesia," International Journal of Energy Economics and Policy, Econjournals, vol. 7(5), pages 245-249.
  20. 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.
  21. Amber, K.P. & Ahmad, R. & Aslam, M.W. & Kousar, A. & Usman, M. & Khan, M.S., 2018. "Intelligent techniques for forecasting electricity consumption of buildings," Energy, Elsevier, vol. 157(C), pages 886-893.
  22. Fernando Dorado Rueda & Jaime Durán Suárez & Alejandro del Real Torres, 2021. "Short-Term Load Forecasting Using Encoder-Decoder WaveNet: Application to the French Grid," Energies, MDPI, vol. 14(9), pages 1-16, April.
  23. Sun-Youn Shin & Han-Gyun Woo, 2022. "Energy Consumption Forecasting in Korea Using Machine Learning Algorithms," Energies, MDPI, vol. 15(13), pages 1-20, July.
  24. Maaouane, Mohamed & Zouggar, Smail & Krajačić, Goran & Zahboune, Hassan, 2021. "Modelling industry energy demand using multiple linear regression analysis based on consumed quantity of goods," Energy, Elsevier, vol. 225(C).
  25. Gejirifu De & Wangfeng Gao, 2018. "Forecasting China’s Natural Gas Consumption Based on AdaBoost-Particle Swarm Optimization-Extreme Learning Machine Integrated Learning Method," Energies, MDPI, vol. 11(11), pages 1-20, October.
  26. Wang, Lin & Lv, Sheng-Xiang & Zeng, Yu-Rong, 2018. "Effective sparse adaboost method with ESN and FOA for industrial electricity consumption forecasting in China," Energy, Elsevier, vol. 155(C), pages 1013-1031.
  27. Diego Lopez-Bernal & David Balderas & Pedro Ponce & Arturo Molina, 2021. "Education 4.0: Teaching the Basics of KNN, LDA and Simple Perceptron Algorithms for Binary Classification Problems," Future Internet, MDPI, vol. 13(8), pages 1-14, July.
  28. Zhang, Chuan & Tian, Yu-Xin & Fan, Zhi-Ping, 2022. "Forecasting sales using online review and search engine data: A method based on PCA–DSFOA–BPNN," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1005-1024.
  29. Xiong, Pingping & Li, Kailing & Shu, Hui & Wang, Junjie, 2021. "Forecast of natural gas consumption in the Asia-Pacific region using a fractional-order incomplete gamma grey model," Energy, Elsevier, vol. 237(C).
  30. Mi, Peiyuan & Zhang, Jili & Han, Youhua & Guo, Xiaochao, 2022. "Operation performance study and prediction of photovoltaic thermal heat pump system engineering in winter," Applied Energy, Elsevier, vol. 306(PB).
  31. Wang, Qiang & Song, Xiaoxin, 2019. "Forecasting China's oil consumption: A comparison of novel nonlinear-dynamic grey model (GM), linear GM, nonlinear GM and metabolism GM," Energy, Elsevier, vol. 183(C), pages 160-171.
  32. Liu, Bingchun & Huo, Xiankai, 2024. "Prediction of Photovoltaic power generation and analyzing of carbon emission reduction capacity in China," Renewable Energy, Elsevier, vol. 222(C).
  33. Liu, Bingchun & Song, Chengyuan & Liang, Xiaoqin & Lai, Mingzhao & Yu, Zhecheng & Ji, Jie, 2023. "Regional differences in China's electric vehicle sales forecasting: Under supply-demand policy scenarios," Energy Policy, Elsevier, vol. 177(C).
  34. Han, Youhua & Ma, Liangdong & Zhang, Jili & Mi, Peiyuan & Guo, Xiaochao, 2024. "Superheat matching control method for a roll-bond photovoltaic-thermal heat pump system," Energy, Elsevier, vol. 290(C).
  35. Peng, Lu & Liu, Shan & Liu, Rui & Wang, Lin, 2018. "Effective long short-term memory with differential evolution algorithm for electricity price prediction," Energy, Elsevier, vol. 162(C), pages 1301-1314.
  36. Jiang, Ping & Yang, Hufang & Li, Hongmin & Wang, Ying, 2021. "A developed hybrid forecasting system for energy consumption structure forecasting based on fuzzy time series and information granularity," Energy, Elsevier, vol. 219(C).
  37. Yingli Wu & Xin Li & Qingquan Liu & Guangji Tong, 2022. "The Analysis of Credit Risks in Agricultural Supply Chain Finance Assessment Model Based on Genetic Algorithm and Backpropagation Neural Network," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1269-1292, December.
  38. Li, Hui & Wu, Zixuan & Yuan, Xing & Yang, Yixuan & He, Xiaoqiang & Duan, Huiming, 2022. "The research on modeling and application of dynamic grey forecasting model based on energy price-energy consumption-economic growth," Energy, Elsevier, vol. 257(C).
  39. Han, Youhua & Ma, Liangdong & Zhang, Jili & Mi, Peiyuan & Guo, Xiaochao, 2023. "Research on the adaptive proportional-integral control method of a direct-expansion photovoltaic-thermal heat pump system," Energy, Elsevier, vol. 281(C).
  40. Yifei Shi & Xinghang Ge & Xueliang Yuan & Qingsong Wang & Jon Kellett & Fangqiu Li & Kaiming Ba, 2019. "An Integrated Indicator System and Evaluation Model for Regional Sustainable Development," Sustainability, MDPI, vol. 11(7), pages 1-23, April.
  41. Daniel Chuquin-Vasco & Francis Parra & Nelson Chuquin-Vasco & Juan Chuquin-Vasco & Vanesa Lo-Iacono-Ferreira, 2021. "Prediction of Methanol Production in a Carbon Dioxide Hydrogenation Plant Using Neural Networks," Energies, MDPI, vol. 14(13), pages 1-18, July.
  42. Xu, Guangyue & Schwarz, Peter & Yang, Hualiu, 2019. "Determining China's CO2 emissions peak with a dynamic nonlinear artificial neural network approach and scenario analysis," Energy Policy, Elsevier, vol. 128(C), pages 752-762.
  43. Mi, Peiyuan & Zhang, Jili & Gao, Jin & Han, Youhua, 2023. "Study on optimal allocation of solar photovoltaic thermal heat pump integrated energy system for domestic hot water," Renewable Energy, Elsevier, vol. 219(P1).
  44. Jing Liu & Chao Zang & Qiting Zuo & Chunhui Han & Stefan Krause, 2023. "Application and Comparison of Different Models for Quantifying the Aquatic Community in a Dam-Controlled River," IJERPH, MDPI, vol. 20(5), pages 1-16, February.
  45. Xiwen Cui & Shaojun E & Dongxiao Niu & Dongyu Wang & Mingyu Li, 2021. "An Improved Forecasting Method and Application of China’s Energy Consumption under the Carbon Peak Target," Sustainability, MDPI, vol. 13(15), pages 1-21, August.
  46. Wang, Lin & Hu, Huanling & Ai, Xue-Yi & Liu, Hua, 2018. "Effective electricity energy consumption forecasting using echo state network improved by differential evolution algorithm," Energy, Elsevier, vol. 153(C), pages 801-815.
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