A5084247175- Rough Sets and Fuzzy Logic
- Multi-Criteria Decision Making
- Complex Network Analysis Techniques
- Cognitive Science and Mapping
- Opinion Dynamics and Social Influence
- Text and Document Classification Technologies
- Elevator Systems and Control
- Bayesian Modeling and Causal Inference
- Power Line Inspection Robots
- Electric Vehicles and Infrastructure
- Fuzzy Logic and Control Systems
- Data Visualization and Analytics
- Cognitive Computing and Networks
- Optimization and Mathematical Programming
- Human Mobility and Location-Based Analysis
- Quality Function Deployment in Product Design
- Complex Systems and Decision Making
- Auction Theory and Applications
- Mechanical stress and fatigue analysis
- Data Management and Algorithms
- Financial Distress and Bankruptcy Prediction
- Mental Health Research Topics
- Vehicle Routing Optimization Methods
- Data Mining Algorithms and Applications
- Corporate Finance and Governance
Hefei University of Technology
2024-2025
Xidian University
2024
University of Electronic Science and Technology of China
2018-2022
In three-way group decision-making based on the minimum risk Bayesian decision theory, consensus of basic loss function evaluation becomes its main core issue. However, if we only consider information consensus, it does not ensure classification quality decisions. Thus, to balance and quality, design a joint learning process via constructing two-stage method. Inspired by supervised learning, Stage 1 establishes error optimization model (MDEOM) learn optimal parameters decisions calculate...
The location selection of charging stations has become the key to implementation popularization electric vehicles. In this article, we introduce AHPSort II method into station. However, does not consider heterogeneity criteria in stations. addition, classification results obtained by are unconstrained, which may meet requirements. Therefore, article proposes a two-stage assignment model based on under heterogeneous criteria. first stage, utilize reduce pairwise comparisons between...
The design of the backstepping control requires setting up a stepping-parameter for every stepping-manifold, making it converge rapidly more importantly. In this article, set variable stepping-parameters are developed control, which is solved by finding optimal solution cost function in receding horizon. designed to remove error between system model and real-world, algorithm called tuning control. Here we discuss series studies on adaptive that, collectively, develop an how eliminated find...
Abstract The sliding mode control has to design a manifold for manipulating the system motion in engineering practice, making asymptotic stability paramount. This is particularly challenging using variable parameters formulate fast convergence and precise control. While much of research on focused constant parameters, comparatively little known about approach parameters. Therefore, are treated as variables computed by parameter tuning algorithm. Regarding algorithm, its input law with output...