A5087588433- Gene Regulatory Network Analysis
- Neural Networks Stability and Synchronization
- Distributed Control Multi-Agent Systems
- Evolution and Genetic Dynamics
- Nonlinear Dynamics and Pattern Formation
- Bioinformatics and Genomic Networks
- Complex Systems and Time Series Analysis
- stochastic dynamics and bifurcation
- Adaptive Control of Nonlinear Systems
- Complex Network Analysis Techniques
- Chaos control and synchronization
- Neural Networks and Applications
- Stability and Control of Uncertain Systems
- Energy Load and Power Forecasting
- Gene expression and cancer classification
- Time Series Analysis and Forecasting
- Teleoperation and Haptic Systems
- Advanced Clustering Algorithms Research
- Mathematical and Theoretical Epidemiology and Ecology Models
- Advanced Graph Neural Networks
- Molecular Communication and Nanonetworks
- Smart Grid and Power Systems
- Mathematical Biology Tumor Growth
- Face and Expression Recognition
- Grey System Theory Applications
Wuhan University of Technology
2016-2025
Shanghai Electric (China)
2024
Tianjin University of Technology and Education
2010-2019
Huazhong University of Science and Technology
2014-2017
Zhejiang University
2010
Kaili University
2009
With the rising geopolitical tensions, predicting future trade partners has become a critical topic for global community. Liquefied natural gas (LNG), recognized as cleanest burning hydrocarbon, plays significant role in transition to cleaner energy future. As international LNG becomes increasingly volatile, it is essential assist governments identifying potential and analyzing network. Traditionally, forecasts of mineral resource networks have relied on similarity indicators (e.g., CN, AA)....
In recent years, computationally assisted diagnosis for classifying autism spectrum disorder (ASD) and typically developing (TD) individuals based on neuroimaging data, such as functional magnetic resonance imaging (fMRI), has garnered significant attention. Studies have shown that long-range connectivity patterns in ASD patients exhibit abnormalities, individual brain networks display considerable heterogeneity. However, current graph neural (GNNs) used research failed to adequately capture...
This paper analyzes the stability and bifurcation criteria of cyclic genetic regulatory networks with mixed time delays (discrete Gamma-type distributed delays). It is more realistic biological background to use delay kernels describe in process between genes. The key aim our research reveal about dynamic functions played by biochemical parameters different mechanisms discrete delays. existence positive equilibria this kind network verified. With mathematical tools subharmonic function...
This paper focuses on the collective dynamics of multisynchronization among heterogeneous genetic oscillators under a partial impulsive control strategy. The coupled nonidentical are modeled by differential equations with uncertainties. definition is proposed to describe some more general synchronization behaviors in real. Considering that each oscillator consists large number biochemical molecules, we design manageable strategy for dynamic networks achieve multisynchronization. Not all...
Forecasting energy demand is critical to ensure the steady operation of power system. However, present approaches estimating load are still unsatisfactory in terms accuracy, precision, and efficiency. In this paper, we propose a novel method, named ELFNet, for short-term electricity consumption, based on deep convolutional neural network model with double-attention mechanism. The Gramian Angular Field method utilized convert electrical time series into 2D image data input proposed model....
Many biological systems have the conspicuous property to present more than one stable state and diverse rhythmic behaviors. A closed relationship between these complex dynamic behaviors cyclic genetic structures has been witnessed by pioneering works. In this paper, a typical structure of inhibitory coupled networks is introduced further enlighten mechanism stability rhythms living cells. The consist two identical subnetworks, which inhibit each other directly. Each subnetwork can be...
Assessing the complexity of signals or dynamical systems is important in disease diagnosis, mechanical system defect, astronomy analysis, and many other fields. Although entropy measures as estimators have greatly improved, majority these are quite sensitive to specified parameters impacted by short data lengths. This paper proposes a novel algorithm enhance existing assessment methods based on classical dispersion (DE) Rényi (RE) introducing refined composite multiscale coarse-grained...
As liver hepatocellular carcinoma (LIHC) has high morbidity and mortality rates, improving the clinical diagnosis treatment of LIHC is an important issue. The advent era precision medicine provides us with new opportunities to cure cancers, including accumulation multi-omics data cancers. Here, we proposed integration method that involved Fisher ratio, Spearman correlation coefficient, classified information index, ensemble decision trees (DTs) for biomarker identification based on...