Computational Intelligence for Fault Detection and Classification

Dear Colleagues,

Computational intelligence has become increasingly important for fault detection and classification in a wide range of systems, including manufacturing processes, power grids, and transportation systems. By analyzing large volumes of data generated by these systems, computational intelligence techniques can identify patterns and detect anomalies that might indicate the presence of faults, errors, or intrusions. These algorithms can also be used to predict when faults might occur, allowing for preventative maintenance and reducing the risk of downtime or safety hazards. In addition, computational intelligence techniques can aid in isolating the cause of a fault, which can be crucial for efficient repairs and minimizing the impact on the overall system. As such, computational intelligence for fault detection and classification represents a promising approach for improving the safety, reliability, and efficiency of complex systems, mainly in this modern interconnected world.

Papers with mathematical analysis and real-world application are particularly welcome.

Topics of interest include but are not limited to:

• Computational intelligence for fault modeling;
• Computational intelligence for fault tolerant control;
• Computational intelligence for fault detection and diagnosis;
• Computational intelligence for fault classification and isolation;
• Computational intelligence for false data injection;
• Computational intelligence in cybersecurity;
• Computational intelligence to detect anomalies;
• Fault detection and classification applied to robotics, dynamic systems, complex networks, biomedical systems, energy systems, industry, transportation, mechatronics, cyber-physical systems, economics and others.

Prof. Dr. Alma Y. Alanis
Guest Editor

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