Area of research
Computer Vision and Pattern Recognition · Civil and Structural Engineering
Research interest
Research focused on Train and Particle swarm optimization, with related work in Residual neural network, Energy consumption, Mean squared error. Notable publications include 'An integrated optimization model of metro energy consumption based on regenerative energy and passenger transfer', 'Tool wear prediction based on convolutional bidirectional LSTM model with improved particle swarm optimization', and 'An improved single-stage convolutional neural network for rail transit obstacle detection'.
CIGCN: a domain generalisation fault diagnosis method for train bearing based on causal inference graph convolutional network
Parallel ResNet-BiGRU tool wear prediction model based on attention mechanism
RLGS-YOLO: an improved algorithm for metro station passenger detection based on YOLOv8
An improved single-stage convolutional neural network for rail transit obstacle detection
Tool wear prediction based on convolutional bidirectional LSTM model with improved particle swarm optimization
An integrated optimization model of metro energy consumption based on regenerative energy and passenger transfer