A5054418935- Opinion Dynamics and Social Influence
- Complex Network Analysis Techniques
- Neural Networks Stability and Synchronization
- EEG and Brain-Computer Interfaces
- Distributed Control Multi-Agent Systems
- ECG Monitoring and Analysis
- Gene Regulatory Network Analysis
- Image Processing Techniques and Applications
- Nonlinear Dynamics and Pattern Formation
- Opportunistic and Delay-Tolerant Networks
- Image and Object Detection Techniques
- Microgrid Control and Optimization
- Energy Load and Power Forecasting
- Power Systems and Renewable Energy
- Non-Invasive Vital Sign Monitoring
- Vehicle License Plate Recognition
- Industrial Vision Systems and Defect Detection
- Neural dynamics and brain function
- Advanced Manufacturing and Logistics Optimization
- Microbial Fuel Cells and Bioremediation
- Software-Defined Networks and 5G
- Inertial Sensor and Navigation
- Control and Dynamics of Mobile Robots
- Guidance and Control Systems
- Brain Tumor Detection and Classification
Qilu University of Technology
2018-2024
Shandong Academy of Sciences
2019-2024
Beihang University
2015-2018
The motor imagery brain–computer interface (MI-BCI) system is currently one of the most advanced rehabilitation technologies, and it can be used to restore function stroke patients. deep learning algorithms in MI-BCI require lots training samples, but electroencephalogram (EEG) data patients quite scarce. Therefore, expansion EEG has become an important part clinical research. In this paper, a convolution generative adversarial network (DCGAN) model proposed generate artificial further...
Abstract Dynamical processes occurring on the edges in complex networks are relevant to a variety of real-world situations. Despite recent advances, framework for edge controllability is still required arbitrary structure and interaction strength. Generalizing previously introduced class dynamics, switchboard exploit- ing exact theory, we develop universal which any node exclusively determined by its local weighted structure. This enables us identify unique set critical nodes control, derive...
Abstract Electrocardiogram (ECG) is mostly used for the clinical diagnosis of cardiac arrhythmia due to its simplicity, non-invasiveness, and reliability. Recently, many models based on deep neural networks have been applied automatic classification with great success. However, most independently extract internal features each lead in 12-lead ECG during training phase, resulting a lack inter-lead features. Here, we propose general model two-dimensional ResNet detached squeeze-and-excitation...
Microbial fuel cells (MFCs) are devices that transform organic matters in wastewater into green energy. systems have strong nonlinearity and high coupling, which involves control science, microbiology, electrochemistry other disciplines. According to the requirements of microbial cell system for model robustness accuracy, we designed a comprehensive optimization framework. Firstly, influence uncertain parameters on was analyzed by combining global sensitivity analysis with uncertainty...
Based on the relationship between capacity and load, cascading failure weighted complex networks is investigated, a load-capacity optimal (LCOR) model proposed in this paper. Compared with three other kinds of linear or non-linear models as well number real-world including railway network, airports network metro LCOR shown to have best robustness against less cost. Furthermore, theoretical analysis computational method its cost threshold are provided validate effectiveness model. The results...
The robustness of controlling complex networks is significant in network science. In this paper, we focus on evaluating and analyzing the edge dynamics against node failure. Using three categories all nodes to quantify robustness, find that percentages types are mainly related degree distribution networks. simulation results model analytic calculations show sparse inhomogeneous networks, which emerge many real have strong control from point number ordinary nodes, but positive correlation...
Edge dynamics is relevant to various real-world systems with complex network topological features. An edge dynamical system controllable if it can be driven from any initial state desired in finite time appropriate control inputs. Here a framework proposed study the impact of correlation between in- and out-degrees on controlling networks. We use maximum matching direct acquisition methods determine controllability limit, i.e., limit acceptable change by adjusting degree only. Applying...
To better track the planned output (forecast output), energy storage systems (ESS) are used by wind farms to compensate forecast error of power and reduce uncertainty output. When compensation degree is same, interval not unique, different intervals need ESS sizing. This paper focused on finding optimal only satisfied but also obtained max profit farm. First, a mathematical model was proposed as well corresponding optimization method aiming at maximizing Second, effect influencing factors...
At present, the railway transport are always held up or even suspended because of natural disasters occurred frequently. In order to guarantee smooth operation and reduce number trains affected by as few possible, proposal train scheduling scheme with optimal invulnerability is proposed in this paper. Firstly, network model based on present China, which real station described a vertex, line an edge, lines designed weight edge. Secondly new indicator measurement regarded object function be...
Abstract Dynamic processes that occur on the edge of complex networks are relevant to a variety real-world systems, where states defined individual edges, and nodes active components with information processing capabilities. In traditional studies controllability, all adjacent assumed be coupled. this paper, we release all-to-all coupling restriction propose general dynamics model. We give theoretical framework study structural controllability find set driver for is unique determined by...
The uncertain and stochastic output of the wind farm results in a lot problems when it is connected to power grid. In order improve power's friendship grid, should has certain self-discipline level. this paper, studied from perspective interval. First, concept interval proposed, followed by comprehensive index which used evaluate level comprehensively considering width accuracy. Second, an optimization method discussed obtain optimal This general applicability, not only suitable for normal...
We use the controllability limit theory to study impact of correlation between in- and out-degrees (degree correlation) on edge real networks. Simulation results analytic calculations show that degree plays an important role in networks, especially dense The upper lower limits hold for all kinds Any is achievable by properly adjusting correlation. In addition, we find dynamics some networks with positive may be difficult control, explain rationality this anomaly based theory.
Dynamical processes occurring on edges of complex networks are relevant to many real situations. Controlling the edge dynamics is a fundamental challenge in network science. Inspired by recent advances controllability theories, we explore role individual classifying each into one three categories: critical, redundant, and intermittent. An analytical framework developed identify category edge, leading discovery that proportions types great extent encoded degree distribution, affected in-...