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Adaptive short-term wind power forecasting with concept drifts Journal article
Li, Yanting, Wu, Zhenyu, Su, Yan. Adaptive short-term wind power forecasting with concept drifts[J]. Renewable Energy, 2023, 217, 119146.
Authors:  Li, Yanting;  Wu, Zhenyu;  Su, Yan
Favorite | TC[WOS]:6 TC[Scopus]:7  IF:9.0/8.1 | Submit date：2023/09/21
Adaptive Prediction  Concept Drift  Feature Extraction  Numerical Weather Prediction  Wind Power Forecasting  Wind Turbine  
Streaming Graph Embeddings via Incremental Neighborhood Sketching Journal article
Yang, Dingqi, Qu, Bingqing, Yang, Jie, Wang, Liang, Cudre-Mauroux, Philippe. Streaming Graph Embeddings via Incremental Neighborhood Sketching[J]. IEEE Transactions on Knowledge and Data Engineering, 2023, 35(5), 5296-5310.
Authors:  Yang, Dingqi;  Qu, Bingqing;  Yang, Jie;  Wang, Liang;  Cudre-Mauroux, Philippe
Favorite | TC[WOS]:3 TC[Scopus]:4  IF:8.9/8.8 | Submit date：2022/05/17
Dynamic Graph Embedding  Streaming Graph  Concept Drift  Data Sketching  Consistent Weighted Sampling  
Mining massive e-health data streams for IoMT enabled healthcare systems Journal article
Affan Ahmed Toor, Muhammad Usman, Farah Younas, Alvis Cheuk M. Fong, Sajid Ali Khan, Simon Fong. Mining massive e-health data streams for IoMT enabled healthcare systems[J]. Sensors (Switzerland), 2020, 20(7), 2131.
Authors:  Affan Ahmed Toor;  Muhammad Usman;  Farah Younas;  Alvis Cheuk M. Fong;  Sajid Ali Khan; et al.
Favorite | TC[WOS]:21 TC[Scopus]:36  IF:3.4/3.7 | Submit date：2021/03/09
Data Stream Mining  Iomt  Concept Drift  Class Imbalance  Machine Learning  
Robust Online Multilabel Learning Under Dynamic Changes in Data Distribution with Labels Journal article
Du, J., Vong, C. M.. Robust Online Multilabel Learning Under Dynamic Changes in Data Distribution with Labels[J]. IEEE Transactions on Cybernetics (SCI-E), 2020, 374-385.
Authors:  Du, J.;  Vong, C. M.
Favorite |   IF:9.4/10.3 | Submit date：2022/08/09
Concept Drift  Dynamic Changes  Multilabel Data Streams  Online Multilabel Learning (Omll)  
Robust Online Multilabel Learning under Dynamic Changes in Data Distribution with Labels Journal article
Du,Jie, Vong,Chi Man. Robust Online Multilabel Learning under Dynamic Changes in Data Distribution with Labels[J]. IEEE Transactions on Cybernetics, 2020, 50(1), 374-385.
Authors:  Du,Jie;  Vong,Chi Man
Favorite | TC[WOS]:19 TC[Scopus]:28  IF:9.4/10.3 | Submit date：2021/03/11
Concept Drift  Dynamic Changes  Multilabel Data Streams  Online Multilabel Learning (Omll)  
Adaptive chunk-based dynamic weighted majority for imbalanced data streams with concept drift Journal article
Lu, Yang, Cheung, Yiu Ming, Yan Tang, Yuan. Adaptive chunk-based dynamic weighted majority for imbalanced data streams with concept drift[J]. IEEE Transactions on Neural Networks and Learning Systems, 2019, 31(8), 2764-2778.
Authors:  Lu, Yang;  Cheung, Yiu Ming;  Yan Tang, Yuan
Favorite | TC[WOS]:42 TC[Scopus]:65  IF:10.2/10.4 | Submit date：2021/12/06
Concept Drift  Ensemble Methods  Imbalance Learning  Online Learning  
Countering the concept-drift problems in big data by an incrementally optimized stream mining model Journal article
Hang Yang, Simon Fong. Countering the concept-drift problems in big data by an incrementally optimized stream mining model[J]. Journal of Systems and Software, 2014, 102, 158-166.
Authors:  Hang Yang;  Simon Fong
Favorite | TC[WOS]:14 TC[Scopus]:23  IF:3.7/3.7 | Submit date：2019/02/13
Concept Drift  Data Stream Mining  Very Fast Decision Tree  
Countering the Concept-drift Problem in Big Data Using iOVFDT Conference paper
Hang Yang, Simon Fong. Countering the Concept-drift Problem in Big Data Using iOVFDT[C]:IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2013, 126-132.
Authors:  Hang Yang;  Simon Fong
Favorite | TC[WOS]:12 TC[Scopus]:16 | Submit date：2019/02/13
Data Stream Mining  Concept Drift  Incremental Decision Tree  Classification