Bøger af Zdzislaw Kowalczuk

The main subject matter of the book is related to the demands of research and industrial centers for diagnostics, monitoring, and decision-making systems that result from the increasing complexity of automation and systems, the need to ensure the highest level of reliability and safety, and continuing research and the development of innovative approaches to fault diagnosis. Most welcome are combinations of domains of engineering knowledge for diagnosis, including detection, isolation, localization, identification, reconfiguration, and fault-tolerant control. This field is open to new challenges, including industrial diagnostics, diagnostics of computer systems and networks, as well as non-industrial applications in the form of medical diagnostics, especially those based on artificial intelligence and deep neural networks.Our community is mainly interested in the following six topics: fault detection, isolation, and identification (FDI); (ii) fault-tolerant control systems; (iii) process safety, quality, and reliability; (iv) medical diagnostics; as well as (v) methodologies based on mathematical modeling, parameter identification and state estimation, qualitative models, statistical and signal processing, artificial intelligence, fuzzy logic and rough sets, expert systems, neural networks; and (vi) industrial applications of diagnostics in fault-tolerant problems, safety, monitoring and alarming, quality control, computer systems and networks, diagnostic software, software reliability, medicine and therapy, environment protection, production control, and other industries such as chemistry, electronics, and power systems. The book is divided into six parts: (I) Artificial Intelligence in Medicine; (II) Cybersecurity; (III) Artificial Neural Networks; (IV) Fault Detection; (V) Systems Modeling; and (VI) Adaptive, Robust and FTC Systems.

This book discusses modeling of management processes in IT, describing initial processing and the maturity capsule, as well as a decision-making system represented by a multi-level sequential model which acquires a fuzzy rule-based implementation in this work.