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Informer-based model predictive control framework considering group controlled hydraulic balance model to improve the precision of client heat load control in district heating system Journal article
Guo, Chengke, Zhang, Ji, Yuan, Han, Yuan, Yonggong, Wang, Haifeng, Mei, Ning. Informer-based model predictive control framework considering group controlled hydraulic balance model to improve the precision of client heat load control in district heating system[J]. Applied Energy, 2024, 373, 123951.
Authors:  Guo, Chengke;  Zhang, Ji;  Yuan, Han;  Yuan, Yonggong;  Wang, Haifeng; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:10.1/10.4 | Submit date：2024/08/05
District Heating System  Hydraulic Balance  Intelligent Heating  Load Forecasting  Model Predictive Control  
A Deep Learning Approach Based on Novel Multi-Feature Fusion for Power Load Prediction Journal article
Xiao, Ling, An, Ruofan, Zhang, Xue. A Deep Learning Approach Based on Novel Multi-Feature Fusion for Power Load Prediction[J]. Processes, 2024, 12(4), 793.
Authors:  Xiao, Ling;  An, Ruofan;  Zhang, Xue
Favorite | TC[WOS]:1 TC[Scopus]:1  IF:2.8/3.0 | Submit date：2024/05/16
Deep Learning Model  Multiple Features  Power Load Forecasting  Transfer Learning  
Accuracy improvement of the load forecasting in the district heating system by the informer-based framework with the optimal step size selection Journal article
Zhang, Ji, Hu, Yuxin, Yuan, Yonggong, Yuan, Han, Mei, Ning. Accuracy improvement of the load forecasting in the district heating system by the informer-based framework with the optimal step size selection[J]. Energy, 2024, 291, 130347.
Authors:  Zhang, Ji;  Hu, Yuxin;  Yuan, Yonggong;  Yuan, Han;  Mei, Ning
Favorite | TC[WOS]:6 TC[Scopus]:7  IF:9.0/8.2 | Submit date：2024/04/02
District Heating System  Informer-based Framework  Intelligent Heating  Load Forecasting  Optimal Step Selection  
When Pre-Training Model Meets Smart Meter Data Applications: A Preliminary Trial of General Way Conference paper
Wang, Zhenyi, Zhang, Hongcai, Zhou, Baorong, Zhao, Wenmeng, Mao, Tian. When Pre-Training Model Meets Smart Meter Data Applications: A Preliminary Trial of General Way[C]:IEEE Computer Society, 2024, 203130.
Authors:  Wang, Zhenyi;  Zhang, Hongcai;  Zhou, Baorong;  Zhao, Wenmeng;  Mao, Tian
Favorite | TC[Scopus]:0 | Submit date：2024/11/05
Deep Learning  Load Forecasting  Load Profiling  Pre-training Model  Smart Meter Data  Transformer  
Short-Term Power Load Forecasting Using MOGOA and ConvBiLSTM During COVID-19 Pandemic Conference paper
Xu, Da, Liu, Bowen, Lam, Chi Seng, Huang, Zhangyou. Short-Term Power Load Forecasting Using MOGOA and ConvBiLSTM During COVID-19 Pandemic[C], 2023.
Authors:  Xu, Da;  Liu, Bowen;  Lam, Chi Seng;  Huang, Zhangyou
Favorite | TC[Scopus]:0 | Submit date：2024/02/22
Coronavirus Disease  Cross-domain  Load Forecasting  
Integrated Load Consumption and PV Output Forecasting of Net-zero Energy Buildings Considering KNN-GAN Data Augmentation Conference paper
Iao Hou Wang, LAO KENG WENG. Integrated Load Consumption and PV Output Forecasting of Net-zero Energy Buildings Considering KNN-GAN Data Augmentation[C], 2023, 399 - 406.
Authors:  Iao Hou Wang;  LAO KENG WENG
Favorite | TC[Scopus]:0 | Submit date：2023/08/29
Gan  Knn  Load Forecasting  Lstm  Net-zero Energy Building  Pv Power Forecasting  Transformer  
Integrated Load Consumption and PV Output Forecasting of Net-zero Energy Buildings Considering KNN-GAN Data Augmentation Conference paper
Iao,Hou Wang, Lao,Keng Weng. Integrated Load Consumption and PV Output Forecasting of Net-zero Energy Buildings Considering KNN-GAN Data Augmentation[C], 2023, 399 - 406.
Authors:  Iao,Hou Wang;  Lao,Keng Weng
Favorite | TC[Scopus]:0 | Submit date：2023/08/03
Gan  Knn  Load Forecasting  Lstm  Net-zero Energy Building  Pv Power Forecasting  Transformer  
Short-term power load interval forecasting based on nonparametric Bootstrap errors sampling Journal article
Xiao, Ling, Li, Miaotong, Zhang, Shenghui. Short-term power load interval forecasting based on nonparametric Bootstrap errors sampling[J]. Energy Reports, 2022, 8, 6672-6686.
Authors:  Xiao, Ling;  Li, Miaotong;  Zhang, Shenghui
Favorite | TC[WOS]:15 TC[Scopus]:16  IF:4.7/5.0 | Submit date：2022/08/02
Adaptive Boosting Algorithm  Extreme Learning Machine  Nonparametric Bootstrap Sampling  Power Load Interval Forecasting  
Learning-based Solar Power and Load Forecasting in DC Net-zero Energy Building with Incomplete Data Conference paper
Hou-Wang Iao, Keng-Weng Lao, Jing Kang. Learning-based Solar Power and Load Forecasting in DC Net-zero Energy Building with Incomplete Data[C], 2022, 583-589.
Authors:  Hou-Wang Iao;  Keng-Weng Lao;  Jing Kang
Favorite | TC[Scopus]:1 | Submit date：2023/01/30
Net-zero Energy Building  Load Forecasting  Pv Power Forecasting  Lstm  
An Adaptive Ensemble Data Driven Approach for Nonparametric Probabilistic Forecasting of Electricity Load Journal article
Wan, Can, Cao, Zhaojing, Lee, Wei Jen, Song, Yonghua, Ju, Ping. An Adaptive Ensemble Data Driven Approach for Nonparametric Probabilistic Forecasting of Electricity Load[J]. IEEE Transactions on Smart Grid, 2021, 12(6), 5396-5408.
Authors:  Wan, Can;  Cao, Zhaojing;  Lee, Wei Jen;  Song, Yonghua;  Ju, Ping
Favorite | TC[WOS]:20 TC[Scopus]:29  IF:8.6/9.6 | Submit date：2021/12/08
Forecasting  Probabilistic Logic  Uncertainty  Predictive Models  Load Forecasting  Load Modeling  Wind Power Generation  Probabilistic Forecasting  Load Forecasting  Data Mining  Uncertainty  Information Entropy  Weighted Resample