AI in Complex Engineering Systems
A special issue of Computers (ISSN 2073-431X). This special issue belongs to the section "AI-Driven Innovations".
Deadline for manuscript submissions: 31 January 2026 | Viewed by 66
Special Issue Editor
Special Issue Information
Dear Colleagues,
The increasing demand for the accurate prediction of performance and maintenance metrics in complex engineering systems has led to a rapid expansion in the application of artificial intelligence (AI). AI methodologies are now routinely employed across a wide range of tasks, including the regression modeling of critical values, the detection of events and anomalies in both numerical and image-based datasets, and the optimization of operational processes. In many cases, these AI-driven approaches have demonstrated superior performance and adaptability when compared to traditional analytical or rule-based methods.
This Special Issue is dedicated to exploring and advancing the use of AI in engineering contexts, with a particular emphasis on fostering interdisciplinary collaboration and increasing the familiarity of engineering-oriented researchers with emerging AI paradigms. The topics of interest include but are not limited to
- Sensor fusion strategies for robust data interpretation;
- Generative models for data augmentation and simulation;
- Multi-agent optimization frameworks for complex control environments;
- Digital twins and AI-enhanced simulation;
- Edge AI implementations for real-time industrial monitoring;
- Explainable AI in engineering decision-making;
- Resilient AI systems for fault-tolerant engineering;
- The application of large language models for tasks such as documentation automation or semantic parsing.
By presenting innovative research across diverse engineering domains, this Special Issue of Computers aims to highlight the transformative potential of AI in the design, monitoring, and optimization of modern engineering systems.
Dr. Sandi Baressi Šegota
Guest Editor
Manuscript Submission Information
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Keywords
- artificial intelligence
- engineering data analytics
- engineering systems
- fault detection and isolation
- industrial automation
- performance modeling
- predictive maintenance
- process optimization
- sensor fusion
- smart manufacturing
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