Description
With the development of artificial intelligence and Internet of Things technologies, the engineering system becomes more and more complex with strong nonlinear dynamics. Since the uncertainness and randomness of the complex systems affect the prediction of traditional model-based designs, the optimization problem has been defined using entropy and stochastic distribution. Based on the recent literature, it has been shown that entropy and stochastic distribution can be considered a design tool for large-scale engineering systems in terms of performance enhancement. Therefore, this Special Issue focuses on this topic to investigate fundamental and applicable results in order to attenuate systemic randomness.
Motivated by this fundamental research topic, the potential applications can be extended using entropy and stochastic distribution, such as the industrial process, transportation system, energy system, manufacturing, networked system, etc. Based upon the developed new results, more practical applications will generate impact on knowledge transfer.
Topics of interest
This topics of interest of this Special Issue include but are not limited to the following research area:
- Machine-learning-based system design, fault diagnosis, tolerant control;
- Data-driven filtering and monitoring for stochastic dynamic systems;
- Stochastic distribution generation via dynamical data sets;
- Entropy optimization and modeling for performance enhancement;
- Nonlinear system control with randomness attenuation;
- Entropy-based image, signal processing and classification;
- Decision-making, management, and planning for stochastic systems;
- Mathematical extensions for entropy analysis.
Submission deadline
Deadline for manuscript submissions: 30 December 2022.
Submission URL
https://www.mdpi.com/journal/entropy/special_issues/entropy_stochastic
Editors
Dr. Qichun Zhang, Department of Computer Science, University of Bradford, Bradford BD7 1DP, UK
Prof. Dr. Chi-Hua Chen, College of Computer and Data Science, Fuzhou University, Fuzhou 350108, China
Prof. Dr. Jianhua Zhang, State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China