A5080316854- Slime Mold and Myxomycetes Research
- Topological and Geometric Data Analysis
- Plant and Biological Electrophysiology Studies
- Biocrusts and Microbial Ecology
- Air Traffic Management and Optimization
- Anomaly Detection Techniques and Applications
- Risk and Safety Analysis
- Fault Detection and Control Systems
- Machine Fault Diagnosis Techniques
- Multi-Criteria Decision Making
- Adversarial Robustness in Machine Learning
- Probabilistic and Robust Engineering Design
- Occupational Health and Safety Research
- Chemical synthesis and alkaloids
- Industrial Vision Systems and Defect Detection
- Digital Transformation in Industry
- Explainable Artificial Intelligence (XAI)
- Human-Automation Interaction and Safety
- Infrastructure Resilience and Vulnerability Analysis
- Engineering Diagnostics and Reliability
- Advanced Graph Neural Networks
- Model Reduction and Neural Networks
- Non-Destructive Testing Techniques
- Bayesian Modeling and Causal Inference
- Sustainable Supply Chain Management
Hong Kong Polytechnic University
2021-2025
Energy Foundation
2023-2024
Xi'an Jiaotong University
2022-2024
Zhejiang Normal University
2023
Jilin University
2022-2023
Vanderbilt University
2014-2021
FedEx (United States)
2020
Southwest University
2012-2017
Qinghai University
2017
Qinghai Normal University
2017
The Job-Shop Scheduling Problem (JSP) is an important concern in advanced manufacturing systems. In real applications, uncertainties exist practically everywhere the JSP, ranging from engineering design to product manufacturing, operating conditions and maintenance. A variety of approaches have been proposed handle uncertain information. Among them, Intuitionistic Fuzzy Sets (IFS) a novel tool with ability vague information widely used many fields. This paper develops method address JSP...
Landing is generally cited as one of the riskiest phases a flight, indicated by much higher accident rate than other flight phases. In this paper, we focus on hard landing problem (which defined touchdown vertical speed exceeding predefined threshold), and build probabilistic predictive model to forecast aircraft's at touchdown, using DASHlink data. Previous work has treated classification problem, where represented categorical variable based threshold. machine learning numerically predict...