Optical Color Computing: Fuzzy Logic and Digital Calculations
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Add to basketVictor Timchenko received his master s degree in Electrical Engineering from Admiral Makarov National University of Shipbuilding (AMNUS) in 1982, his philosophy of doctorate degree in Design of Ships from AMNUS in 1988, and his doctor of science d.
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This River Publishers Rapid monograph explores recent advances in intelligent technologies and optical computing methods for real-time decision-making systems handling large arrays of fuzzy input data. Developed through long-term collaboration between scientists in Ukraine and the United States―including teams from the University of Texas at El Paso, Admiral Makarov National University of Shipbuilding, Petro Mohyla Black Sea National University, and the Institute of Artificial Intelligence Problems―this work is presented in two focused chapters: Fundamentals of Optical Computing and Optical Color Computing Architecture in Digital Support Systems.
The book examines the principles of optical computing, fuzzy data processing, and logical operations based on color representation as an information set. It introduces an innovative approach that uses light radiation of specific colors as fuzzy variables―enhancing the efficiency and speed of logical systems through optical parallelism.
Practical implementation of this architecture is demonstrated through a decision support model for managing intensive sea and air traffic, illustrating how real-time multifactorial fuzzy color databases can improve operational decision-making. Performance evaluations show that optical computation delivers higher processing speed due to fewer required operations and parallel data structures.
These results have broad applications for higher education, large enterprises, and infrastructure facilities―such as airports, seaports, and oil and gas terminals―where artificial intelligence systems support automated control and decision-making.
Victor Timchenko received his master's degree in Electrical Engineering from Admiral Makarov National University of Shipbuilding (AMNUS) in 1982, his philosophy of doctorate degree in Design of Ships from AMNUS in 1988, and his doctor of science degree in Automation Control from Odessa National Polytechnic University in 2013. He is currently working as a Professor at the Department of Computer Engineering at Automation and Electrical Institute of AMNUS. His research areas include robust optimal control systems, optical architecture and computing, and decision support systems.
Vladik Kreinovich is Professor of Computer Science, University of Texas at El Paso, El Paso, Texas, USA, Vice President of International Fuzzy Systems Association (IFSA), Vice President of European Society of Fuzzy Logic and Technology (EUSFLAT), and AT&T Fellow in Information Technology. His areas of interest are interval computations, intelligent control (including fuzzy and neural approaches), and reasoning under uncertainty. He is the author of more than 1500 publications.
Yuriy Kondratenko is a Doctor of Science, Professor, Honour Inventor of Ukraine (2008), Corr. Academician of Royal Academy of Doctors (Barcelona, Spain), Head of the Department of Intelligent Information Systems at Petro Mohyla Black Sea National University (PMBSNU), Ukraine, Leading Researcher of the Institute of Artificial Intelligence Problems of MES and NAS of Ukraine, and Fulbright Scholar. He received a Ph.D. (1983) and Dr.Sc. (1994) at Odessa National Polytechnic University, and several international grants and scholarships for conducting research at P.R. of China, Germany, and the USA. He has been guest editor of 3 special issues of River Publishers’ Journal of Mobile Multimedia and an editor of several River Publishers’ monographs, including Advances in Intelligent Robotics and Collaborative Automation (2015), Control Systems: Theory and Applications (2018), Advanced Control Systems: Theory and Applications (2021), Recent Developments in Automatic Control Systems (2022) and Research Tendencies and Prospect Domains for AI Development and Implementation (2024). His research interests include robotics, automation, sensors and control systems, intelligent decision support systems, and fuzzy logic.
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