EDBT 2026 Demo / reviewers in the wild / expert
Di Liu 0012
dblp:15/1777-12
· DBLP profile ↗
3ranked-venue papers in the field
1as first author
2since 2021 · last 2025
0000-0002-8232-4089ORCID · verified
Domains — venue-derived; a paper can count in several
Other / Interdisciplinary · 2Knowledge Engineering, Semantic Web & Information Systems · 1 (1 first)
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | A degradation modeling method based on artificial neural network supported Tweedie exponential dispersion process
Zhongze He, Shaoping Wang, Di Liu 0012 |
Adv. Eng. Informatics | 3 |
| 2025 | A Multiobjective Optimization Method for Collecting and Releasing Processes of Winch System Considering Wave Disturbance and Control LawsabstractThe winch’s performance under complex sea conditions is significantly influenced by its collecting and releasing processes. To enhance its performance and reliability, an optimization approach considering wave disturbances and control laws is proposed to balance time efficiency and tension stability. Within a multiobjective optimization framework, the method designs constant tension control and robust adaptive speed control and introduces sinusoidal acceleration trajectories to minimize tension surges and reduce system impacts caused by rapid starts/stops. The constant tension controller reduces wave disturbances, while the speed controller manages the working process. These controllers are designed with unknown reference signals determined during the optimization process. Additionally, the objective functions in the optimization phase aim to reduce working time and tension fluctuations, with constraints ensuring system safety and mission requirements. Furthermore, an experimental platform constructed on a ship validates the accuracy of the winch model. The optimized process not only shortens operational time, as collecting same length only consumption 127.44 s compared 143.14 s without optimization, but also reduces tension and acceleration. More importantly, transitions between states become more gradual. This indicates that the proposed method is both time‐efficient and effective in dampening tension fluctuations and mitigating the effects of abrupt changes during the working process. Xiaochuan Duan, Shaoping Wang, Di Liu 0012, Yaoxing Shang |
Int. J. Intell. Syst. | 4 |
| 2020 | An evidence theory based model fusion method for degradation modeling and statistical analysis
Di Liu 0012, Shaoping Wang, Mileta M. Tomovic, Chao Zhang 0027 |
Inf. Sci. | 1 |