Changgen Li

11 papers Journal 10Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
A Hybrid Deep Reinforcement Learning Framework for Vehicle Path Optimization with Time Windows.
Algorithms
Zhiguo Xiao, Changgen Li, Junli Liu, Xinyao Cao
2026 J jnl
DFS-TSPML: Distribution Feature Screening and Three-Stage Physical Information Meta-Learning for Multi-Condition Tool Wear Monitoring.
IEEE Trans Autom. Sci. Eng.
Yuncong Lei, Changgen Li, Zhichao You, Ao Cao, Liang Guo, Hongli Gao
2025 J jnl
Enhanced multi-breed cattle face recognition in complex environments using attention-based deep learning.
Vis. Comput.
Zhiguo Xiao, Wenxin Dai, Changgen Li, Wenhui Liang, Xianqing Chen
2025 J jnl
VBTCKN: A Time Series Forecasting Model Based on Variational Mode Decomposition with Two-Channel Cross-Attention Network.
Symmetry
Zhiguo Xiao, Changgen Li, Huihui Hao, Siwen Liang, Qi Shen, Dongni Li
2024 J jnl
A Temporal-Spatial Framework for Efficient Heat Flux Monitoring of Transient Boiling.
IEEE Trans. Instrum. Meas.
Christy Dunlap, Changgen Li, Hari Pandey, Ying Sun, Han Hu
2024 J jnl
BubbleID: A Deep Learning Framework for Bubble Interface Dynamics Analysis.
CoRR
Christy Dunlap, Changgen Li, Hari Pandey, Ngan Le, Han Hu
2024 J jnl
GMM-BinSeg: A Data Segmentation Method for CFRP/Aluminum Stacks Drilling- Countersinking Monitoring Signal.
IEEE Trans. Instrum. Meas.
Changgen Li, Yuncong Lei, Liang Guo, Enrico Zio, Hongli Gao, Baocheng Yang
2023 J jnl
A Novel Evaluation Metric Based on Dispersion of Wear Distance for In Situ Tool Condition Monitoring.
IEEE Trans. Instrum. Meas.
Zhichao You, Shichao Li, Changgen Li, Hongli Gao, Liang Guo, Yuekai Liu
2023 J jnl
Vision-Based Defect Measurement of Drilled CFRP Composites Using Double-Light Imaging.
IEEE Trans. Instrum. Meas.
Changgen Li, Yuncong Lei, Zhichao You, Liang Guo, Enrico Zio, Hongli Gao
2021 — conf
A Transfer Learning Based Method for Incipient Fault Detection.
ICPS
Changgen Li, Liang Guo, Hongli Gao, Junhao Yang, Xun Dong, Zhichao You
2021 J jnl
Similarity-Measured Isolation Forest: Anomaly Detection Method for Machine Monitoring Data.
IEEE Trans. Instrum. Meas.
Changgen Li, Liang Guo, Hongli Gao, Yi Li