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Time-Varying ADN Load Modeling Considering the Suppression of the Plateau Phenomenon and Continuous Low-Quality Data Journal article
Wang, Peng, Zhang, Zhenyuan, Chen, Chenxu, Huang, Qi, Dai, Ningyi, Lee, Wei Jen. Time-Varying ADN Load Modeling Considering the Suppression of the Plateau Phenomenon and Continuous Low-Quality Data[J]. IEEE Transactions on Industry Applications, 2024, 60(5), 7451-7460.
Authors:  Wang, Peng;  Zhang, Zhenyuan;  Chen, Chenxu;  Huang, Qi;  Dai, Ningyi; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:4.2/4.5 | Submit date：2024/11/05
Active Distribution Network  Continuous Low-quality Data  Improved Synthesis Load Model  Target Parameter Selection  Time-varying Parameter Identification  
A Multistep Interval Prediction Method Combining Environmental Variables and Attention Mechanism for Egg Production Rate Journal article
Yin, Hang, Wu, Zeyu, Wu, Jun Chao, Chen, Yalin, Chen, Mingxuan, Luo, Shixuan, Gao, Lijun, Hassan, Shahbaz Gul. A Multistep Interval Prediction Method Combining Environmental Variables and Attention Mechanism for Egg Production Rate[J]. Agriculture (Switzerland), 2023, 13(6), 1255.
Authors:  Yin, Hang;  Wu, Zeyu;  Wu, Jun Chao;  Chen, Yalin;  Chen, Mingxuan; et al.
Favorite | TC[WOS]:2 TC[Scopus]:2 | Submit date：2023/07/20
Egg Production Rate  Environmental Variables Selection  Gwo-vmd Decomposition  Interval Prediction  Mogwo Optimize Parameter  Multistep Point Prediction  Seq2seq-attention  
Bayesian Real-Time System Identification: From Centralized to Distributed Approach Book
Huang, Ke, Yuen, Ka Veng. Bayesian Real-Time System Identification: From Centralized to Distributed Approach[M]. Singapore:Springer, 2023, 276.
Authors:  Huang, Ke;  Yuen, Ka Veng
Favorite | TC[Scopus]:3 | Submit date：2024/01/10
Bayesian Inference  Centralized Identification  Distributed Identification  Model Class Selection  Parameter Estimation  Real-time System Identification  Structural Health Monitoring  
A Novel Time-Varying Parameter Identification Approach for Load Model in Active Distribution Network Conference paper
Peng Wang, Zhenyuan Zhang, Qi Huang, Ningyi Dai, Wei-Jen Lee. A Novel Time-Varying Parameter Identification Approach for Load Model in Active Distribution Network[C], 2022.
Authors:  Peng Wang;  Zhenyuan Zhang;  Qi Huang;  Ningyi Dai;  Wei-Jen Lee
Favorite | TC[Scopus]:1 | Submit date：2023/01/30
Active Distribution Network  Improved Synthesis Load Model  Time-varying Parameter Identification  Target Parameter Selection  Continuous Low-quality Data  
Model selection for RBF-ARX models Journal article
Chen, Qiong Ying, Chen, Long, Su, Jian Nan, Fu, Ming Jian, Chen, Guang Yong. Model selection for RBF-ARX models[J]. Applied Soft Computing, 2022, 121, 108723.
Authors:  Chen, Qiong Ying;  Chen, Long;  Su, Jian Nan;  Fu, Ming Jian;  Chen, Guang Yong
Favorite | TC[WOS]:7 TC[Scopus]:9  IF:7.2/7.0 | Submit date：2022/06/10
Model Selection  Genetic Algorithms  Parameter Estimation  Rbf-arx Models  Time Series Prediction  Variable Projection  
Training Feed-Forward Artificial Neural Networks with a modified artificial bee colony algorithm Journal article
Xu,Feiyi, Pun,Chi Man, Li,Haolun, Zhang,Yushu, Song,Yurong, Gao,Hao. Training Feed-Forward Artificial Neural Networks with a modified artificial bee colony algorithm[J]. Neurocomputing, 2020, 416, 69-84.
Authors:  Xu,Feiyi;  Pun,Chi Man;  Li,Haolun;  Zhang,Yushu;  Song,Yurong; et al.
Favorite | TC[WOS]:20 TC[Scopus]:26  IF:5.5/5.5 | Submit date：2021/03/11
Artificial Bee Colony  Deep Learning  Feed-forward Artificial Neural Networks  Parameter Selection  
Optimizing SMOTE by Metaheuristics with Neural Network and Decision Tree Conference paper
Jinyan Li, Simon Fong, Yan Zhuang. Optimizing SMOTE by Metaheuristics with Neural Network and Decision Tree[C]:IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2016, 26-32.
Authors:  Jinyan Li;  Simon Fong;  Yan Zhuang
Favorite | TC[WOS]:19 TC[Scopus]:33 | Submit date：2019/02/13
Smote  Swarm Intelligence  Parameter Selection Optimization  
Cluster number selection for a small set of samples using the Bayesian Ying-Yang model Journal article
Guo P., Chen C.L.P., Lyu M.R.. Cluster number selection for a small set of samples using the Bayesian Ying-Yang model[J]. IEEE Transactions on Neural Networks, 2002, 13(3), 757-763.
Authors:  Guo P.;  Chen C.L.P.;  Lyu M.R.
Favorite | TC[WOS]:61 TC[Scopus]:65 | Submit date：2019/02/11
Bootstrap  Cluster Number Selection  Data Smoothing  Sem Algorithm  Small Number Sample Set  Smoothing Parameter Estimation