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Ensemble empirical mode decomposition and long short-term memory neural network for multi-step predictions of time series signals in nuclear power plants

Citations

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  1. Junfeng Wu & Hanyu Chen & Xu Li & Guohua Kang & Yuangang Lu, 2022. "Correlation coefficient local capping REMD adaptive filtering method for laser interference signal," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-12, January.
  2. Zhe Dong & Zhonghua Cheng & Yunlong Zhu & Xiaojin Huang & Yujie Dong & Zuoyi Zhang, 2023. "Review on the Recent Progress in Nuclear Plant Dynamical Modeling and Control," Energies, MDPI, vol. 16(3), pages 1-19, February.
  3. Chang, Ling & Yu, Haibo & Yang, Minghan & Zhang, Ziheng & Chen, Shuai & Wang, Jianye, 2026. "NPP-GPT: Forecasting nuclear power plants operating parameters using pre-trained large language model," Applied Energy, Elsevier, vol. 409(C).
  4. Qiao, Weibiao & Fu, Zonghua & Du, Mingjun & Nan, Wei & Liu, Enbin, 2023. "Seasonal peak load prediction of underground gas storage using a novel two-stage model combining improved complete ensemble empirical mode decomposition and long short-term memory with a sparrow search algorithm," Energy, Elsevier, vol. 274(C).
  5. Hongtao Li & Xiaoxuan Li & Shaolong Sun & Zhipeng Huang & Xiaoyan Jia, 2024. "Multivariable forecasting approach of high‐speed railway passenger demand based on residual term of Baidu search index and error correction," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2401-2433, November.
  6. Parvaiz Ahmad Ahangar & Shameem Ahmad Lone & Neeraj Gupta, 2023. "Combining Data-Driven and Model-Driven Approaches for Optimal Distributed Control of Standalone Microgrid," Sustainability, MDPI, vol. 15(16), pages 1-19, August.
  7. Xiao, Xiao & Song, Meiqi & Liu, Xiaojing, 2025. "A reliable and adaptive prediction framework for nuclear power plant system through an improved Transformer model and Bayesian uncertainty analysis," Reliability Engineering and System Safety, Elsevier, vol. 261(C).
  8. Lu, Peng & Ye, Lin & Zhao, Yongning & Dai, Binhua & Pei, Ming & Tang, Yong, 2021. "Review of meta-heuristic algorithms for wind power prediction: Methodologies, applications and challenges," Applied Energy, Elsevier, vol. 301(C).
  9. Zizhen Cheng & Li Wang & Yumeng Yang, 2023. "A Hybrid Feature Pyramid CNN-LSTM Model with Seasonal Inflection Month Correction for Medium- and Long-Term Power Load Forecasting," Energies, MDPI, vol. 16(7), pages 1-18, March.
  10. Duan, Wenshun & Zhang, Kefan & Wang, Weixiang & Dong, Sifan & Pan, Rui & Qin, Chong & Chen, Hongli, 2025. "Parameter prediction of lead-bismuth fast reactor under various accidents with recurrent neural network," Applied Energy, Elsevier, vol. 378(PA).
  11. Zhao, Yuan & Zhang, Weiguo & Gong, Xue & Wang, Chao, 2021. "A novel method for online real-time forecasting of crude oil price," Applied Energy, Elsevier, vol. 303(C).
  12. Huang, Qingyu & Zeng, Wei & Liu, Jia & Zhang, Zhuo & Deng, Jian & Qiu, Zhifang & Xu, Le & Wei, Zonglan & Lu, Qi & Gong, Lanxin & Shi, Chunsen & Zhong, Xianping, 2025. "Shaping the future of nuclear reactors with digital twins: Current developments and perspectives," Applied Energy, Elsevier, vol. 402(PA).
  13. Pinciroli, Luca & Baraldi, Piero & Zio, Enrico, 2023. "Maintenance optimization in industry 4.0," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
  14. Xiao, Xiao & Zhang, Xuan & Song, Meiqi & Liu, Xiaojing & Huang, Qingyu, 2024. "NPP accident prevention: Integrated neural network for coupled multivariate time series prediction based on PSO and its application under uncertainty analysis for NPP data," Energy, Elsevier, vol. 305(C).
  15. Yu, Haibo & Chang, Ling & Yang, Minghan & Chen, Shuai & Li, Huijuan & Wang, Jianye, 2025. "Time series modeling and forecasting with feature decomposition and interaction for prognostics and health management in nuclear power plant," Energy, Elsevier, vol. 324(C).
  16. Lin, Yu & Liao, Qidong & Lin, Zixiao & Tan, Bin & Yu, Yuanyuan, 2022. "A novel hybrid model integrating modified ensemble empirical mode decomposition and LSTM neural network for multi-step precious metal prices prediction," Resources Policy, Elsevier, vol. 78(C).
  17. Cheng, Wei & Ahmad, Hassaan & Gao, Lin & Xing, Ji & Nie, Zelin & Chen, Xuefeng & Xu, Zhao & Zhang, Rongyong, 2025. "Diagnostics and Prognostics in Power Plants: A systematic review," Reliability Engineering and System Safety, Elsevier, vol. 255(C).
  18. Nadimi, Reza & Goto, Mika, 2025. "Uncertainty reduction in power forecasting of virtual power plant: From day-ahead to balancing markets," Renewable Energy, Elsevier, vol. 238(C).
  19. Wang, Chu & Dou, Manfeng & Li, Zhongliang & Outbib, Rachid & Zhao, Dongdong & Zuo, Jian & Wang, Yuanlin & Liang, Bin & Wang, Peng, 2023. "Data-driven prognostics based on time-frequency analysis and symbolic recurrent neural network for fuel cells under dynamic load," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
  20. Nadimi, Reza & Goto, Mika, 2025. "A novel decision support system for enhancing long-term forecast accuracy in virtual power plants using bidirectional long short-term memory networks," Applied Energy, Elsevier, vol. 382(C).
  21. Zhong, Weiyi & Zhai, Dengshuai & Xu, Wenran & Gong, Wenwen & Yan, Chao & Zhang, Yang & Qi, Lianyong, 2024. "Accurate and efficient daily carbon emission forecasting based on improved ARIMA," Applied Energy, Elsevier, vol. 376(PA).
  22. Sibtain, Muhammad & Li, Xianshan & Saleem, Snoober & Ain, Qurat-ul- & Shi, Qiang & Li, Fei & Saeed, Muhammad & Majeed, Fatima & Shah, Syed Shoaib Ahmed & Saeed, Muhammad Hammad, 2022. "Multifaceted irradiance prediction by exploiting hybrid decomposition-entropy-Spatiotemporal attention based Sequence2Sequence models," Renewable Energy, Elsevier, vol. 196(C), pages 648-682.
  23. Yang, Kailing & Zhang, Xi & Luo, Haojia & Hou, Xianping & Lin, Yu & Wu, Jingyu & Yu, Liang, 2024. "Predicting energy prices based on a novel hybrid machine learning: Comprehensive study of multi-step price forecasting," Energy, Elsevier, vol. 298(C).
  24. Wang, Fuqing & Wang, Kun & Tang, Lixin & Wang, Chun & Li, Kunlun, 2026. "Multi-physics field study of CO low-temperature catalytic reactor based on CFD-GNN approach," Energy, Elsevier, vol. 347(C).
  25. Guan, Shouping & Xu, Chongyang & Guan, Tianyi, 2025. "Multistep interval prediction model with adjustable horizon for uncertain power load forecasting," Energy, Elsevier, vol. 335(C).
  26. Hamid Nasiri & Mohammad Mehdi Ebadzadeh, 2022. "Multi-step-ahead Stock Price Prediction Using Recurrent Fuzzy Neural Network and Variational Mode Decomposition," Papers 2212.14687, arXiv.org.
  27. Jia, Xiongjie & Sang, Yichen & Li, Yanjun & Du, Wei & Zhang, Guolei, 2022. "Short-term forecasting for supercharged boiler safety performance based on advanced data-driven modelling framework," Energy, Elsevier, vol. 239(PE).
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