The Springer publishing house has released the volume “System Analysis and Data Mining”, which brings together research articles by Ukrainian and international scholars under the general editorship of Academician Michael Zgurovsky and Corresponding Member of the National Academy of Sciences of Ukraine Nataliya Pankratova. The book is part of the Studies in Systems, Decision and Control series and represents the results of long-term interdisciplinary cooperation aimed at advancing system analysis and data mining within the context of current global challenges. It demonstrates the extent to which system analysis and data mining have become methodological foundations for studying and addressing complex problems—from environmental security and forecasting the dynamics of natural and social processes to applications of artificial intelligence and machine learning.
System analysis and big data now constitute essential scientific tools for investigating natural, technical, and socio-economic systems. The increasing interconnectedness of global processes, the emergence of new types of risks, the rapid growth of available data, and the demand for more accurate forecasting models underscore the need for integrated scientific approaches. In this context, the volume “System Analysis and Data Mining” serves as an example of a systematic synthesis of contemporary methods in modelling, computation, and data analytics.
The materials presented in the book cover modelling the dynamics of complex ecological and social systems, assessing the consequences of armed conflicts, analysing instabilities, multi-criteria decision-making approaches, and mathematical methods that form the basis of modern artificial intelligence algorithms. Considerable attention is devoted to hybrid intelligent systems that combine neural networks, fuzzy logic, and adaptive models, thereby expanding opportunities for working with objects characterised by complex or partially uncertain structure.
The sections devoted to data mining demonstrate the application of intelligent data-analysis methods to the study of socio-economic processes, risk assessment in financial and environmental systems, land-use change analysis, and the construction of digital models and forecasting tools. These materials highlight the need to integrate analytical, mathematical, and computational methods within a unified research framework.
The volume confirms the important role of the Ukrainian school of system analysis in the global scientific discourse and demonstrates the contribution of Ukrainian researchers to the development of modelling, forecasting, and big-data analysis methods. Under current conditions, intellectual potential remains a key resource that enables the continuity of scientific development and supports Ukraine’s participation in shaping a contemporary research paradigm grounded in interdisciplinarity and analytical rigour.
In a broader methodological sense, system analysis and data mining function not only as research instruments but also as approaches for structuring and interpreting complexity. They make it possible to consider multi-level processes as components of integrated systems, to model their dynamics, and to formulate evidence-based decisions in economics, ecology, engineering, and public administration. The works presented in the volume provide a comprehensive view of the current state of system research and outline directions for its further development.
The book “System Analysis and Data Mining” may be of interest to researchers working in system analysis, machine learning, complex-systems modelling, and data analytics, as well as to practitioners involved in decision-making in applied fields that rely on forecasting models and intelligent information-processing methods.