A5005860501- Reinforcement Learning in Robotics
- Electricity Theft Detection Techniques
- Robotic Path Planning Algorithms
- Energy Load and Power Forecasting
- Adversarial Robustness in Machine Learning
- Anomaly Detection Techniques and Applications
- Brain Tumor Detection and Classification
- E-commerce and Technology Innovations
- Distributed Control Multi-Agent Systems
- Power Systems and Technologies
- Power Transformer Diagnostics and Insulation
Fujian Normal University
2024
China Southern Power Grid (China)
2020
Brain tumor detection has advanced significantly with the development of deep learning technology. Although multimodal data, such as Magnetic Resonance Imaging (MRI) and Computed Tomography (CT), potential advantages in diagnostics, most existing studies rely solely on a single modality. This is because common fusion methods may lead to loss critical information when attempting fusion. Therefore, effectively integrating data become significant challenge. Additionally, medical image analysis...
Reinforcement learning (RL) is pivotal in empowering Unmanned Aerial Vehicles (UAVs) to navigate and make decisions efficiently intelligently within complex dynamic surroundings. Despite its significance, RL hampered by inherent limitations such as low sample efficiency, restricted generalization capabilities, a heavy reliance on the intricacies of reward function design. These challenges often render single-method approaches inadequate, particularly context UAV operations where high costs...
In the domain of reinforcement learning (RL), deriving efficacious state representations and maintaining algorithmic stability are crucial for optimal agent performance. However, inherent dynamism often complicates normalization procedure. To overcome these challenges, we present an innovative RL framework that integrates techniques with residual connections incorporates attention mechanisms into generative adversarial imitation (GAIL). This combination not only enhances expressive...
Abstract The construction of Ubiquitous Power Internet Things expands the content and scale data in distribution network. In order to meet demand intelligent operation maintenance terminals, this paper proposes a method mining association rules realize evaluation terminal units. method, firstly, Apriori algorithm with directional constraint terminals’ functional module is used mine correlation indicators system under each divided terminals. Secondly, comprehensive measurement confidence lift...
Abstract As the condition monitoring and control device in distribution automation system, abnormal or fault state of terminal units’ measurement system will negatively affect quality measured electrical quantities, therefore, fast accurate discrimination state’s data improve reliability system. This paper proposes a method, which is based on generative adversarial network (GAN) combined with convolutional neural (CNN), to discriminate specific category terminals’ measuring data. Firstly,...