The Fusion of Deep Reinforcement Learning and Edge Computing for Real-time Monitoring and Control Optimization in IoT Environments.

Automatic driving lane change safety prediction model based on LSTM.

Application of Machine Learning Optimization in Cloud Computing Resource Scheduling and Management.

Progress in artificial intelligence applications based on the combination of self-driven sensors and deep learning.

Energy-Efficient Data and Energy Integrated Management Strategy for IoT Devices Based on RF Energy Harvesting.

Adaptive energy saving algorithms for Internet of Things devices integrating end and edge strategies.