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Post-boosting of classification boundary for imbalanced data using geometric mean Journal article
NEURAL NETWORKS, 2017,Volume: 96,Page: 101-114
Authors:  Du, Jie;  Vong, Chi-Man;  Pun, Chi-Man;  Wong, Pak-Kin;  Ip, Weng-Fai
Favorite  |  View/Download:28/0  |  Submit date:2018/10/30
Imbalance Learning  Boosting  Weighted Elm  Smote  
Prediction Intervals for Landslide Displacement Based on Switched Neural Networks Journal article
IEEE Transactions on Reliability, 2016,Volume: 65,Issue: 3,Page: 1483-1495
Authors:  Lian C.;  Philip Chen C.L.;  Zeng Z.;  Yao W.;  Tang H.
Favorite  |  View/Download:0/0  |  Submit date:2019/02/11
Extreme learning machine (ELM)  landslide displacement prediction  prediction intervals (PIs)  switched prediction  
Representational learning for fault diagnosis of wind turbine equipment: A multi-layered extreme learning machines approach Journal article
Energies, 2016,Volume: 9,Issue: 6
Authors:  Yang Z.-X.;  Wang X.-B.;  Zhong J.-H.
Favorite  |  View/Download:2/0  |  Submit date:2018/12/22
Autoencoder (Ae)  Classification  Extreme Learning Machines (Elm)  Fault Diagnosis  Wind Turbine  
A Robust AdaBoost.RT Based Ensemble Extreme Learning Machine Journal article
Mathematical Problems in Engineering, 2015,Volume: 2015
Authors:  Zhang P.;  Yang Z.
Favorite  |  View/Download:3/0  |  Submit date:2018/12/22
ELM Based Representational Learning for Fault Diagnosis of Wind Turbine Equipment Conference paper
Proceedings of ELM-2015, Hangzhou, China, Dec 2015
Authors:  Zhixin Yang;  Xianbo Wang;  Pak Kin Wong;  Jianhua Zhong
Favorite  |  View/Download:2/0  |  Submit date:2019/04/02
Fault Diagnosis  Autoencoder  Wind Turbine  Representational Learning  Classification  Extreme Learning Machines