A5100757101- Advanced Algorithms and Applications
- Microgrid Control and Optimization
- Energy Efficient Wireless Sensor Networks
- Advanced Sensor and Control Systems
- Power Systems and Renewable Energy
- Smart Grid Energy Management
- High-Voltage Power Transmission Systems
- Smart Grid and Power Systems
- Electric Vehicles and Infrastructure
- HVDC Systems and Fault Protection
- Advanced Battery Technologies Research
- Power Systems and Technologies
- Advanced Computational Techniques and Applications
- Industrial Technology and Control Systems
- Real-Time Systems Scheduling
- Distributed and Parallel Computing Systems
- Power System Optimization and Stability
- Mobile Ad Hoc Networks
- Optimal Power Flow Distribution
- Cloud Computing and Resource Management
- Power Systems Fault Detection
- Metaheuristic Optimization Algorithms Research
- Integrated Energy Systems Optimization
- Indoor and Outdoor Localization Technologies
- Stability and Control of Uncertain Systems
Guizhou University
2016-2025
Fujian University of Technology
2014-2025
Guangdong Ocean University
2025
Kwangwoon University
2024
Kunming University of Science and Technology
2010-2024
Chongqing University
2009-2024
Liaoning Technical University
2023-2024
Southwest University of Science and Technology
2021-2024
Hubei University of Technology
2021-2024
Beijing Institute of Radio Metrology and Measurement
2023-2024
Improving the accuracy of power system load forecasting is important for economic dispatch. However, a sequence highly nonstationary and hence makes accurate difficult. In this paper, method based on wavelet decomposition (WD) second-order gray neural network combined with an augmented Dickey-Fuller (ADF) test proposed to improve forecasting. First, decomposed by WD reduce sequence. Then, ADF adopted as stationary each component after in which results determine best level. Finally, because...
Knowledge graph alignment aims to link equivalent entities across different knowledge graphs. To utilize both the structures and side information such as name, description attributes, most of works propagate especially names through linked by neural networks. However, due heterogeneity graphs, accuracy will be suffered from aggregating neighbors. This work presents an interaction model only leverage information. Instead neighbors, we compute interactions between neighbors which can capture...
The unmanned surface vehicle (USV) is usually required to perform some tasks with the help of static and dynamic environmental information obtained from different detective systems such as shipborne radar, electronic chart, AIS system. essential requirement for USV safe when suffered an emergency during task. However, it has been proved be difficult maritime traffic becoming more complex. Consequently, path planning collision avoidance become a hot research topic in recent year. This paper...
Selection of the kernel function by support vector regression (SVR), for purposes load forecasting, is affected power characteristics. The non-ideal SVR with a has low forecasting accuracy and poor generalization ability. A novel method combining stacking proposed in this paper. Base models are constructed based on SVRs different functions, then multiple base merged to obtain model layer via algorithm. Finally, an connected as meta-model layer. fusion composed This trained k-fold cross...
A new prediction framework is proposed to improve short-term power load forecasting accuracy. The based on particle swarm optimization (PSO)-variational mode decomposition (VMD) combined with a time convolution network (TCN) embedded attention mechanism (Attention). follows two-step process. In the first step, PSO applied optimize VMD method. original electricity sequence decomposed, and fitness function uses sample entropy describe complexity of series. decomposed sub-sequences are relevant...
Based on density functional theory, the adsorption behavior of seven typical dissolved gas molecules (CO, CO
This paper addresses the three-dimensional trajectory tracking problem of underactuated autonomous underwater vehicles (AUVs) operating in presence external disturbances and unmodeled dynamics by proposing a predefined-time adaptive control scheme. Firstly, AUV system was decoupled into drive non-drive subsystems to facilitate design controller that does not rely on specific model parameters. Radial basis function neural networks (RBFNNs) were employed estimate disturbances. To enhance...
Vehicular ad hoc networks (VANETs) are wireless self-organizing networks, whose communication is conducted through open channels, thus making it vulnerable to various attacks. It therefore necessary employ encryption technology ensure secure communication. In view of the foregoing, key agreement techniques introduced VANET communications. The group (GKA) protocol allows a participants establish public session for channel over an insecure network. traditional GKA inefficient, however, and...
To address the problems of uneven distribution and low coverage wireless sensor network (WSN) nodes in random deployment, a node optimization strategy with an improved COOT bird algorithm (COOTCLCO) is proposed. Firstly, chaotic tent map used to initialize population, increase diversity lay foundation for global search optimal solutions. Secondly, Lévy flight perturb individual positions improve range population. Thirdly, Cauchy mutation opposition-based learning are fused solutions generate...
Aiming at the problem that power load data are stochastic and it is difficult to obtain accurate forecasting results by a single algorithm, in this paper, combined method for short-term was proposed based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN)-sample entropy (SE), BP neural network (BPNN), Transformer model. Firstly, were decomposed into several subsequences obvious complexity differences using CEEMDAN-SE. Then, BPNN model used forecast low high...
In the Industrial Internet of Things (IIoT), wireless sensor network (WSN) technology makes devices that communicate with each other. The information integrated from multiple data sources will be transformed into productivity. However, clusters close to base station take a considerable load over multi-hop transmission, and in this case, lifetime industrial WSN is restricted. To solve problem, grid-based clustering algorithm via analysis for IIoT presented paper. First, quantitatively...
Integrating renewable energy into power grids is seen in increase recent years since these sources are sustainable and clean. However, the integration brings about considerable technical challenges associated with fluctuations uncertainties of availability whilst maintaining stability smart grids. The prediction generation key to achieve optimal dispatch renewable-intensive uncertain interruption errors will make an decision more challenging. Model predictive control (MPC) effective way...