INFORMATION AND CONTROL SYSTEMS: MODELLING AND OPTIMIZATIONS
Olexander Litvinenko, Svitlana Kashkevich, Andrii Shyshatskyi, Oksana Dmytriieva, Serhii Neronov, Ganna Plekhova, Yevhen Zhyvylo, Nina Kuchuk, Oleksii Kuvshynov, Oleksandr Yefymenko, Andrii Veretnov, Heorhii Kuchuk, Viacheslav Davydov, Yurii Beketov, Illia Dmytriiev, Inna Shevchenko, Oleksandr Lytvynenko, Lyubov Shabanova-Kushnarenko, Nataliia Apenko
The high dynamism of the development of social processes and phenomena determines the formation of a new system of the worldview of mankind, the modification (change) of the hierarchy of needs and values, and challenges to the pace and quality of development.
Solving complex problems associated with meeting the requirements of our time requires the use of innovative scientific approaches. Today, the use of modern intellectual technologies, such as neural networks, deep learning, and artificial intelligence, is a prerequisite for the proactive development of all spheres of human activity: medicine, technology, business, environmental protection, education, transport and communication, etc. Thus, the intellectualization of technical and managerial systems can be considered one of the key foundations of the new paradigm of science and technology. The phrase “artificial intelligence systems” today is understandable to everyone. The context of this term is associated with such concepts as robotics, forecasting, processing of large information flows, expert systems, diagnostics, smart home or smart tools projects, cyberphysical space and cyberphysical systems, computer translation, etc.
There is a positive dynamics in the development and implementation of artificial intelligence elements in most types of software: mobile applications, information systems, electronic devices, etc.
This process of “intellectualization” allows us to talk about a gradual increase in the intelligence of modern computer systems capable of performing functions that are traditionally considered intellectual: understanding language, logical inference, using the accumulated knowledge, learning, pattern recognition, as well as learning and explaining their decisions.
The monograph provides methods for training artificial neural networks that have an adaptive structure and can evolve. They are set out in a separate section in the study. These methods are used by the authors in further studies to reduce errors that accumulate during the solution of optimization problems.
A separate section presents the issue of self-organization of information networks, using artificial intelligence methods. This study is aimed at solving the scientific and applied problem in terms of increasing the efficiency of self-organization of information networks at the first four levels of the model of interaction of open systems.
Separate sections include issues of evaluation and management of organizational and technical systems. These methods are based on metaheuristic algorithms. Assessment of the state of organizational and technical systems makes it possible to determine their state, taking into account the type of uncertainty about the available information, about their state, and in the future to develop adequate and reliable management decisions, taking into account the noise (distortion) of the data circulating in the organizational and technical system
The authors’ research is supported by appropriate analytical expressions, graphic dependencies, and table values.
The monograph will be useful for researchers involved in solving optimization problems, using the theory of artificial intelligence, and developing new (improving existing) approaches to solving complex technical problems in various fields of human activity.
The monograph is also useful for practitioners – designers, developers implementing modern solutions in the field of information technology, engaged in the development of information, information and analytical, as well as automated systems to create new schemes and algorithms, their adaptation to non-stereotypical conditions of use, including for the implementation of artificial intelligence methods in the conditions of autonomous work, limitation of computing resources, remote control, etc.
How to cite paper:
Shyshatskyi, A. (Ed.) (2024). Information and control systems: modelling and optimizations: collective monograph. Kharkiv: ТЕСHNOLOGY СЕNTЕR PC, 180. doi: http://doi.org/10.15587/978-617-8360-04-7