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Change of global land extreme temperature in the future Journal article
Zhang, Xinlong, Huang, Taosheng, Wang, Weiping, Shen, Ping. Change of global land extreme temperature in the future[J]. Global and Planetary Change, 2024, 242, 104583.
Authors:  Zhang, Xinlong;  Huang, Taosheng;  Wang, Weiping;  Shen, Ping
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:4.0/4.5 | Submit date：2024/10/10
Climate Change  Cmip6  Extreme Temperatures  Multi-model Ensemble  
An Integrated Fusion Framework for Ensemble Learning Leveraging Gradient Boosting and Fuzzy Rule-Based Models Journal article
Li, Jinbo, Liu, Peng, Chen, Long, Pedrycz, Witold, Ding, Weiping. An Integrated Fusion Framework for Ensemble Learning Leveraging Gradient Boosting and Fuzzy Rule-Based Models[J]. IEEE Transactions on Artificial Intelligence, 2024.
Authors:  Li, Jinbo;  Liu, Peng;  Chen, Long;  Pedrycz, Witold;  Ding, Weiping
Favorite | TC[Scopus]:0 | Submit date：2024/08/05
Fuzzy Rules-based Model  Incremental Models  Interpretability  Ensemble Learning  
Parameter-Free Robust Ensemble Framework of Fuzzy Clustering Journal article
Shi,Zhaoyin, Chen,Long, Ding,Weiping, Zhang,Chuanbin, Wang,Yingxu. Parameter-Free Robust Ensemble Framework of Fuzzy Clustering[J]. IEEE Transactions on Fuzzy Systems, 2023, 31(12), 4205-4219.
Authors:  Shi,Zhaoyin;  Chen,Long;  Ding,Weiping;  Zhang,Chuanbin;  Wang,Yingxu
Favorite | TC[WOS]:7 TC[Scopus]:8  IF:10.7/9.7 | Submit date：2023/08/03
Clustering Algorithms  Clustering Ensemble  Computational Efficiency  Costs  Fluctuations  Fuzzy Clustering  Latent Information  Matrix Decomposition  Optimization  Parameter-free Model  Spectral Feature  Tensors  
Modality-Collaborative AI Model Ensemble for Lung Cancer Early Diagnosis Conference paper
Xu, Wanxing, Kuang, Yinglan, Wang, Lin, Wang, Xueqing, Guo, Qiaomei, Ye, Xiaodan, Fu, Yu, Yang, Xiaozheng, Zhang, Jinglu, Ye, Xin, Lu, Xing, Lou, Jiatao. Modality-Collaborative AI Model Ensemble for Lung Cancer Early Diagnosis[C]:SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY, 2022, 91-99.
Authors:  Xu, Wanxing;  Kuang, Yinglan;  Wang, Lin;  Wang, Xueqing;  Guo, Qiaomei; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2023/01/30
Artificial Intelligence  Cancer Diagnostic Model  Early Lung Cancer Diagnosis  Low-dose Ct  Model Ensemble  
Learning multimodal parameters: A bare-bones niching differential evolution approach Journal article
Gong Yuejiao, Zhang Jun, Zhou Yicong. Learning multimodal parameters: A bare-bones niching differential evolution approach[J]. IEEE Transactions on Neural Networks and Learning Systems, 2018, 29(7), 2944-2959.
Authors:  Gong Yuejiao;  Zhang Jun;  Zhou Yicong
Favorite | TC[WOS]:41 TC[Scopus]:44 | Submit date：2018/12/21
Fitness Landscape  Gaussian Model  Multimodal Optimization (Mmop)  Neighborhood Strategy  Neural Network Ensemble (Nne)  Niching  
Learning Multimodal Parameters: A Bare-Bones Niching Differential Evolution Approach Journal article
Gong, Yue-Jiao, Zhang, Jun, Zhou, Yicong. Learning Multimodal Parameters: A Bare-Bones Niching Differential Evolution Approach[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 29(7), 2944-2959.
Authors:  Gong, Yue-Jiao;  Zhang, Jun;  Zhou, Yicong
Favorite | TC[WOS]:41 TC[Scopus]:44  IF:10.2/10.4 | Submit date：2018/10/30
Fitness Landscape  Gaussian Model  Multimodal Optimization (Mmop)  Neighborhood Strategy  Neural Network Ensemble (Nne)  Niching  
Data-driven train operation models based on data mining and driving experience for the diesel-electric locomotive Journal article
Zhang C.-Y., Chen D., Yin J., Chen L.. Data-driven train operation models based on data mining and driving experience for the diesel-electric locomotive[J]. Advanced Engineering Informatics, 2016, 30(3), 553-563.
Authors:  Zhang C.-Y.;  Chen D.;  Yin J.;  Chen L.
Favorite | TC[WOS]:20 TC[Scopus]:26 | Submit date：2019/02/13
Automatic Train Operation  Data-driven Train Operation Model  Ensemble Learning  Machine Learning  Manual Driving  
Ensemble Forecasting of Value at Risk via Multi Resolution Analysis based Methodology in Metals Markets Journal article
He, Kaijian, Lai, Kin Keung, Yen, Jerome. Ensemble Forecasting of Value at Risk via Multi Resolution Analysis based Methodology in Metals Markets[J]. EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39(4), 4258-4267.
Authors:  He, Kaijian;  Lai, Kin Keung;  Yen, Jerome
Favorite | TC[WOS]:18 TC[Scopus]:20  IF:7.5/7.6 | Submit date：2019/12/05
Time Series Model  Nonlinear Ensemble Algorithm  Value At Risk  Neural Network  Wavelet Analysis  Multi Resolution Analysis