邵小锐｜贵州大学｜学者主页

2026

EnergyFormer: dual-supervised adaptive multi-scale Transformer for multistep energy forecasting

Xiaorui Shao, Ruizhang Huang, Yongbin Qin

Expert Systems With Applications，Vol. 305

DOI

2026

Multi-step Industrial Energy Consumption Forecasting with Heterogeneous Feature Grouping and Direct Multi-Output Strategy

Yue Qin, Jian-Ming Yang, Xiaorui Shao

2026 IEEE International Conference on Pattern Recognition, Machine Vision and Artificial Intelligence (PRMVAI)

DOI

2025

Multi-branch global Transformer-assisted network for fault diagnosis

Xiaorui Shao, C. Kim

Applied Soft Computing

DOI

2024

Adaptive multi-scale attention convolution neural network for cross-domain fault diagnosis

Xiaorui Shao, Chang-Soo Kim

Expert Systems With Applications，Vol. 236

DOI

2024

TFFS: A trainable federal fusion strategy for multistep time series forecasting

Xiaorui Shao, C. Kim

Information Sciences

DOI

2024

DSMT-1DCNN: Densely supervised multitask 1DCNN for fault diagnosis

Xiaorui Shao, De Li, Ilkyeun Ra, Chang-Soo Kim

Knowledge-Based Systems

DOI

2023

DL-MSCNN: a general and lightweight framework for fault diagnosis with limited training samples

Xiaorui Shao, Ah-Ri Lee, C. Kim

Journal of Intelligent Manufacturing

DOI

2022

Unsupervised Domain Adaptive 1D-CNN for Fault Diagnosis of Bearing

Xiaorui Shao, C. Kim

Italian National Conference on Sensors

DOI

2022

Accurate Multi-Site Daily-Ahead Multi-Step PM2.5 Concentrations Forecasting Using Space-Shared CNN-LSTM

Xiaorui Shao, Chang Soo Kim

Computers Materials & Continua

DOI

2021

Highly Accurate Short-term Gas Consumption and Elapsed Time Forecasting Using Multi-Channel Deep Neural Network

Ye-Rim Choi, Xiaorui Shao, Hyungun Hwang

IEEE Access

DOI

2021

Fault Diagnosis of Bearing Based on Convolutional Neural Network Using Multi-Domain Features

Xiaorui Shao, Lijiang Wang, C. Kim, Ilkyeun Ra

KSII Transactions on Internet and Information Systems

DOI

2020

Accurate Multi-Scale Feature Fusion CNN for Time Series Classification in Smart Factory

Xiaorui Shao, Chang Soo Kim, Dae Geun Kim

Computers Materials & Continua

DOI

2020

Domain Fusion CNN-LSTM for Short-Term Power Consumption Forecasting

Xiaorui Shao, Chen Pu, Yuxin Zhang, C. Kim

IEEE Access

DOI

2020

Multi-Step Short-Term Power Consumption Forecasting Using Multi-Channel LSTM With Time Location Considering Customer Behavior

Xiaorui Shao, C. Kim

IEEE Access

DOI

2020

Accurate Deep Model for Electricity Consumption Forecasting Using Multi-channel and Multi-Scale Feature Fusion CNN–LSTM

Xiaorui Shao, Chang-So Kim, Palash Sontakke

Energies

DOI

2019

Fault Detection of Electric Vehicle Charging Pile on Basis of CNN-LSTM

Chang-So Kim, Xiaorui Shao

邵小锐

精选作品

期刊论文

EnergyFormer: dual-supervised adaptive multi-scale Transformer for multistep energy forecasting

Multi-step Industrial Energy Consumption Forecasting with Heterogeneous Feature Grouping and Direct Multi-Output Strategy

Multi-branch global Transformer-assisted network for fault diagnosis

Adaptive multi-scale attention convolution neural network for cross-domain fault diagnosis

TFFS: A trainable federal fusion strategy for multistep time series forecasting

DSMT-1DCNN: Densely supervised multitask 1DCNN for fault diagnosis

DL-MSCNN: a general and lightweight framework for fault diagnosis with limited training samples

Unsupervised Domain Adaptive 1D-CNN for Fault Diagnosis of Bearing

Accurate Multi-Site Daily-Ahead Multi-Step PM2.5 Concentrations Forecasting Using Space-Shared CNN-LSTM

Highly Accurate Short-term Gas Consumption and Elapsed Time Forecasting Using Multi-Channel Deep Neural Network

Fault Diagnosis of Bearing Based on Convolutional Neural Network Using Multi-Domain Features

Accurate Multi-Scale Feature Fusion CNN for Time Series Classification in Smart Factory

Domain Fusion CNN-LSTM for Short-Term Power Consumption Forecasting

Multi-Step Short-Term Power Consumption Forecasting Using Multi-Channel LSTM With Time Location Considering Customer Behavior

Accurate Deep Model for Electricity Consumption Forecasting Using Multi-channel and Multi-Scale Feature Fusion CNN–LSTM

Fault Detection of Electric Vehicle Charging Pile on Basis of CNN-LSTM

研究方向