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Ke Yan
Ke Yan
Professor, Mechanical and Electrical Engineering, Hunan University, National University of Singapore
Zweryfikowany adres z nus.edu.sg - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
A hybrid feature selection algorithm for gene expression data classification
H Lu, J Chen, K Yan, Q Jin, Y Xue, Z Gao
Neurocomputing 256, 56-62, 2016
3972016
Short-Term Photovoltaic Power Forecasting Based on Long Short Term Memory Neural Network and Attention Mechanism
H Zhou, K Yan, Y Du
IEEE Access 7, 78063-78074, 2019
3892019
Hierarchical Adversarial Attacks Against Graph Neural Network Based IoT Network Intrusion Detection System
X Zhou, W Liang, W Li, K Yan, S Shimizu, KIK Wang
IEEE Internet of Things Journal, 2021
2472021
A hybrid LSTM neural network for energy consumption forecasting of individual households
K Yan, W Li, Z Ji, M Qi, Y Du
Ieee Access 7, 157633-157642, 2019
2412019
Multi-step short-term power consumption forecasting with a hybrid deep learning strategy
K Yan, X Wang, Y Du, N Jin, H Huang, H Zhou
Energies 11 (11), 3089, 2018
1932018
Generative adversarial network for fault detection diagnosis of chillers
K Yan, A Chong, Y Mo
Building and Environment 172, 106698, 2020
1882020
ARX model based fault detection and diagnosis for chillers using support vector machines
K Yan, W Shen, T Mulumba, A Afshari
Energy and Buildings 81, 287-295, 2014
1802014
Unsupervised learning for fault detection and diagnosis of air handling units
K Yan, J Huang, W Shen, Z Ji
Energy and Buildings 210, 2019
1692019
Semi-supervised learning for early detection and diagnosis of various air handling unit faults
K Yan, C Zhong, Z Ji, J Huang
Energy and Buildings 181, 75-83, 2018
1692018
Robust model-based fault diagnosis for air handling units
T Mulumba, A Afshari, K Yan, W Shen, LK Norford
Energy and Buildings 86, 698-707, 2015
1632015
Online fault detection methods for chillers combining extended kalman filter and recursive one-class SVM
K Yan, Z Ji, W Shen
Neurocomputing 228, 205-212, 2016
1542016
Cost-sensitive and sequential feature selection for chiller fault detection and diagnosis
K Yan, L Ma, Y Dai, W Shen, Z Ji, D Xie
International Journal of Refrigeration 86, 401-409, 2017
1532017
Mathematical and Computational Modeling in Complex Biological Systems
Z Ji, K Yan, W Li, H Hu, X Zhu
BioMed Research International, 2017
1232017
Highly accurate energy consumption forecasting model based on parallel LSTM neural networks
N Jin, F Yang, Y Mo, Y Zeng, X Zhou, K Yan, X Ma
Advanced Engineering Informatics 51, 101442, 2022
1222022
Multi-task learning model based on multi-scale CNN and LSTM for sentiment classification
N Jin, J Wu, X Ma, K Yan, Y Mo
IEEE Access 8, 77060-77072, 2020
1192020
A hybrid deep learning technology for PM2.5 air quality forecasting
Z Zhang, Y Zeng, K Yan
Environmental Science and Pollution Research 28, 39409-39422, 2021
1182021
Multivariate Air Quality Forecasting with Nested LSTM Neural Network
N Jin, Y Zeng, K Yan, Z Ji
IEEE Transactions on Industrial Informatics, 2021
1112021
Edge-enabled two-stage scheduling based on deep reinforcement learning for internet of everything
X Zhou, W Liang, K Yan, W Li, I Kevin, K Wang, J Ma, Q Jin
IEEE Internet of Things Journal 10 (4), 3295-3304, 2022
1102022
Fast and accurate classification of time series data using extended ELM: Application in fault diagnosis of air handling units
K Yan, Z Ji, H Lu, J Huang, W Shen, Y Xue
IEEE Transactions on Systems, Man, and Cybernetics: Systems 49 (7), 1349-1356, 2019
1092019
Chiller fault diagnosis based on VAE-enabled generative adversarial networks
K Yan, J Su, J Huang, Y Mo
IEEE Transactions on Automation Science and Engineering 19 (1), 387-395, 2020
1082020
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