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Xiaorui Shao
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2020 – today
- 2024
- [j11]Xiaorui Shao
, Chang-Soo Kim
:
Adaptive multi-scale attention convolution neural network for cross-domain fault diagnosis. Expert Syst. Appl. 236: 121216 (2024) - [j10]Xiaorui Shao, Chang-Soo Kim:
TFFS: A trainable federal fusion strategy for multistep time series forecasting. Inf. Sci. 679: 121126 (2024) - [j9]Xiaorui Shao
, De Li
, Ilkyeun Ra, Chang-Soo Kim
:
DSMT-1DCNN: Densely supervised multitask 1DCNN for fault diagnosis. Knowl. Based Syst. 292: 111609 (2024) - 2022
- [j8]Xiaorui Shao
, Chang Soo Kim
:
An Adaptive Job Shop Scheduler Using Multilevel Convolutional Neural Network and Iterative Local Search. IEEE Access 10: 88079-88092 (2022) - [j7]Yuming Li, Wei Zhang, Yanyan Liu, Xiaorui Shao:
A lightweight network for real-time smoke semantic segmentation based on dual paths. Neurocomputing 501: 258-269 (2022) - [j6]Xiaorui Shao
, Chang-Soo Kim:
Unsupervised Domain Adaptive 1D-CNN for Fault Diagnosis of Bearing. Sensors 22(11): 4156 (2022) - 2021
- [j5]Yeonjee Choi
, Xiaorui Shao
, Hyun Suk Hwang:
Highly Accurate Short-Term Gas Consumption and Elapsed Time Forecasting Using Multi-Channel Deep Neural Network. IEEE Access 9: 157447-157457 (2021) - [j4]Xiaorui Shao
, Lijiang Wang, Chang Soo Kim, Ilkyeun Ra:
Fault Diagnosis of Bearing Based on Convolutional Neural Network Using Multi-Domain Features. KSII Trans. Internet Inf. Syst. 15(5): 1610-1629 (2021) - [j3]Xiaorui Shao
, Chang Soo Kim:
Self-Supervised Long-Short Term Memory Network for Solving Complex Job Shop Scheduling Problem. KSII Trans. Internet Inf. Syst. 15(8): 2993-3010 (2021) - 2020
- [j2]Xiaorui Shao
, Chang Soo Kim
:
Multi-Step Short-Term Power Consumption Forecasting Using Multi-Channel LSTM With Time Location Considering Customer Behavior. IEEE Access 8: 125263-125273 (2020) - [j1]Xiaorui Shao
, Chen Pu
, Yuxin Zhang
, Chang Soo Kim
:
Domain Fusion CNN-LSTM for Short-Term Power Consumption Forecasting. IEEE Access 8: 188352-188362 (2020)
Coauthor Index
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last updated on 2024-07-25 19:33 CEST by the dblp team
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