Information Processing and Optimization in Control Solutions

1. Auflage 2026
ISBN: 978-87-438-1252-4
Verlag: River Publishers

Buch, Englisch, 354 Seiten, Format (B × H): 156 mm x 234 mm

Reihe: River Publishers Series in Computing and Information Science and Technology

This monograph presents significant scientific advances across intelligent control, information processing, optimization, optimal set partitioning, and modern numerical methods. It explores both classical and emerging techniques, with emphasis on neural networks, machine learning, contextual data analysis, large-scale data processing, cloud computing, and computational methods.

The theoretical developments are complemented by a wide range of practical applications. These include modeling the dynamics of financial markets, solving complex logistics tasks, and addressing technical challenges in 3D printing. The work also highlights solutions of direct practical relevance, such as information system design for cybersecurity, digital platforms for optimizing military personnel training, and data-driven diagnostic methods for assessing the human body under high physical stress. Additionally, the monograph examines optimal scheduling techniques and software development for analyzing unstructured time series.

The content is organized into three integrated parts: Artificial Intelligence and Control Solutions, Advances in Optimization Theory, and Information Processing Techniques and Their Applications. Together, these sections offer a comprehensive perspective for researchers and professionals working with intelligent systems, computational technologies, and applied problem solving.

Zielgruppe

Academic, Postgraduate, and Professional Practice & Development

Autoren/Hrsg.

P. Kondratenko, Yuriy

O. Chikrii, Arkadii

M. Kiseleva, Elena

N. Salnikov, Nikolay

Fachgebiete

• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Part 1. Artificial Intelligence and Control Solutions 1 Normalization Invariance: A New Approach to Foundations of Fuzzy Control 2 Practical Analysis of Solutions to Optimize the Computational Requirements of Neural Models 3 Exploring Machine Learning Methods for Fuzzy Logic-based Sentiment Analysis of Written Context 4 Comparative Analysis of Object Detection Models on Different Dataset Sizes 5 Deep Learning-Based Fire and Smoke Detection for Safety Systems 6 Hybrid Missing Data Imputation Method Based on Regression and Entropy Approach 7 Financial Forecasting Strategies: Integrating Data-driven Approaches and Advanced Models Part 2. Advances in Optimization Theory 8 Two-stage Proximal Algorithms for Equilibrium and Optimization Problems in Hadamard Spaces 9 Solving Geospatial Analysis and Logistics Problems Based on the Synthesis of Optimal Set Partitioning Methods and Cluster Analysis 10 Three Variants of the Generalized Ellipsoid Method 11 On One Procedure for Generating Aggregate e-subgradients 12 Justification of the Feasibility of Allowing Interruptions in a Single Scheduling Theory Problem 13 Using Discrete and Continuous Algorithms to Build Optimal Trajectories in 3D Printing  Part 3. Information Processing Techniques and Their Applications 14 Universal Soft Computing Models: Division of Triangular Fuzzy Numbers with Various Asymmetrical Shapes 15 Intelligent System for Optimizing the Training of Female Military Personnel 16 Development of a Mixed Reality Fitness Game with Real-world Objects Interaction 17 Application of Deployment Models Cloud Technology 18 Information Processing for Assessing the Body's Adaptation Capabilities to Increased Loads 19 Business Analysis of a Mobile Application for Learning Classical Music

Über Autor(innen)

Yuriy P. Kondratenko is a Doctor of Science, Professor, Honour Inventor of Ukraine (2008), Corr. Academician of Royal Academy of Doctors (Barcelona, Spain), Corr. Academician of Royal Academy of Economic and Finance Sciences (Spain), Head of the Department of Intelligent Information Systems at Petro Mohyla Black Sea National University (PMBSNU), Leading Researcher at the Institute of Artificial Intelligence Problems of Ministry of Education and Science and National Academy of Sciences of Ukraine, Ukraine. He has received a Ph.D. (1983) and Dr.Sc. (1994) in Elements and Devices of Computer and Control Systems from Odessa National Polytechnic University, several international grants and scholarships for conducting research at Institute of Automation of Chongqing University, P.R.China (1988–1989), Ruhr-University Bochum, Germany (2000, 2010), Nazareth College and Cleveland State University, USA (2003), and a Fulbright Scholarship for researching in USA (2015/2016) at the Dept. of Electrical Engineering and Computer Science in Cleveland State University. Research interests include robotics, automation, sensors and control systems, intelligent decision support systems, and fuzzy logic.

Arkadii Chikrii is a Doctor of Science, Professor, Academician of the National Academy of Sciences of Ukraine, Head of the Department of Optimization of Controlled Processes at Glushkov Institute of Cybernetics of NASU. He received his Ph.D. in 1972 and Dr.Sc. in 1979. A. Chikrii is the Editor in Chief of the International Scientific Technical Journal “Problems of Control and Informatics” and the Chief of Ukrainian Association on Automatic Control (Ukrainian Branch of IFAC). He is an Editor of two River Publishers monographs “Advanced Control Systems: Theory and Applications” (2021) and “Developments in Automatic Control Systems” (2022). His research interests are focused on extremal problems, mathematical theory of control, nonlinear analysis and dynamic games.

Elena Kiseleva is Doctor of Science,