Engineering Applications of Hybrid Artificial Intelligence Tools
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 10 September 2025 | Viewed by 3460
Special Issue Editors
Interests: eye tracking; image processing; neural networks with fractional derivative; pilot attention analysis; control; spacecraft formation; state estimation; scheduling of discrete production processes; control algorithms
Special Issues, Collections and Topics in MDPI journals
Interests: aircraft systems; vision system; flight simulator, eye tracking; HMI systems; image processing; neural networks; control
Special Issues, Collections and Topics in MDPI journals
Interests: scheduling of discrete production processes; control algorithms; neural networks; control; knowledge base; multistage decision process; 3-D scenery analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The interest in artificial intelligence leads to the consolidation of the activities of scientists and the education of the best experts from the broad activities in this field, so that the work of independent global centers can inspire their creators and find business applications faster. The development of simulation environments with a standardized API interface will allow for the collection of a large amount of data derived from interacting with the environment using AI methods in the branches of management, automation, robotics, autonomous vehicles, or energy consumption control. The use of fuzzy logic methods, evolutionary calculations, and neural networks in intelligent decision support and control systems (e.g., intelligent systems and machine learning methods for searching and processing information and supporting decision-making) allows for the optimal design of engineering systems. It seems important to use deep machine learning methods to recognize early symptoms of damage to physical objects based on the activity of their real processes and to automatically detect anomalies in multidimensional production systems. Research on machine learning, statistical inference, and information theory, including variable selection methods in high-dimensional classification problems, will allow for smooth communication and detailed data exchange in algorithmic AI systems.
What is common to the aforementioned areas of modern AI is the fact that they utilize the multidisciplinary nature of artificial intelligence, combining diverse achievements from “pure disciplines” such as computer science, mathematics, physics, automation, electronics, biology, genetics, medicine, aviation, and many others. The hybrid nature of the developed solutions gives them enormous commercial potential, encompassing the extremely important human component of the discoveries made, while simultaneously serving as a key element for the rapid development of technologies for Industry 5.0. Hence, the hybrid application of AI in engineering underscores the Special Issue to which we cordially invite all authors.
Dr. Zbigniew Gomolka
Dr. Damian Kordos
Prof. Dr. Ewa Dudek-Dyduch
Guest Editors
Manuscript Submission Information
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Keywords
- learning strategy
- distributed optimization algorithms design and analysis
- data-based modeling and control for optimization complex system
- intelligent technologies for optimizing discrete processes
- AI technologies for human–computer interaction
- eyetracking technologies
- multi-task and multi-objective optimization
- AI applications for software engineering
- neural networks and deep learning
- hybrid and hierarchical intelligent systems
- hybrid artificial intelligence tools
- multi-agent systems
- knowledge representation and management
- preprocessing of industry processes data for DNN
- AI for eyetracking technology
- intelligent scheduling for discrete processes
- intelligent technologies for UAV fleets including monitoring and management
- AI applications in aviation systems
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