Defense of the dissertation of Akynbekova Aiman for the degree of Doctor of Philosophy (PhD) in the specialty «8D06103 - Information systems»

L.N. Gumilyov Eurasian National University, a dissertation defense for the degree of Doctor of Philosophy (PhD) by Akynbekova Aiman on the topic «Implementation of fuzzy decision-making models in social processes» to the educational program «8D06103 – Information systems».

The dissertation was carried out at the «Information Systems education department» of L.N. Gumilyov Eurasian National University.

The language of defense is kazakh

Official reviewers:

Temporary members of the Dissertation Committee:

Scientific advisors:

Ayagoz Mukhanova – PhD, Associate Professor of the Department of Information Systems, L.N. Gumilyov Eurasian National University (Astana, Republic of Kazakhstan);

Al-Majeed Salah – Doctor of Philosophy (PhD), Dean and Professor of the School of Science and Engineering, Al Akhawayn University (Ifrane, Morocco).

The defense will take place on August 28, 2026, at 12:00 PM in the Dissertation Council for the training direction «8D061 – Information and communication technologies» in the specialty «8D06103 – Information systems» of L.N. Gumilyov Eurasian National University. The defense meeting is planned to be held online.

Link: https://teams.microsoft.com/meet/45534449523050?p=K8AlZJpZfsub61Nj2j

Address: г. Астана, ул. Пушкина, 11, Учебный корпус № 2, аудитория № 222. г.

Abstract (English): ABSTRACT of the dissertation work by Aiman Akynbekova on the topic « Implementation of fuzzy decision-making models in social processes» submitted for the degree of Doctor of Philosophy (PhD) under the educational program «8D06103 - Information Systems» Relevance of the study. In the modern era, issues of social and socio-economic development in the Republic of Kazakhstan are a priority area of ​​state policy. Ensuring the country's sustainable development, improving the quality of life of the population, reducing socio-economic inequality between regions, and enhancing governance effectiveness are clearly reflected in the Republic of Kazakhstan's long-term strategic documents. In particular, the "Kazakhstan-2050" Strategy, the National Development Plan until 2025, and the "Digital Kazakhstan" state program specifically emphasize the need for widespread implementation of data-driven digital and intelligent solutions in social management. These strategic documents emphasize the scientific validity of management decisions, their comprehensiveness, and flexibility as essential conditions for the implementation of regional policy and the social sphere. However, the multifactorial nature of social processes, the heterogeneity of indicators, the simultaneous use of qualitative and quantitative information, and the high level of uncertainty and subjectivity complicate effective decision-making using traditional deterministic and statistical methods. This circumstance necessitates the search for new methodological approaches to the analysis and management of social processes. In the context of digitalization, the processing of large volumes of heterogeneous data, its integration, and interpretation in public and regional governance systems are becoming increasingly important. Expert assessments and qualitative characteristics play a particularly important role in decision-making in socially significant areas such as quality of life, accessibility of social infrastructure, healthcare, education, housing policy, ecology, and communications. In this regard, models based on fuzzy logic are viewed as a promising tool for formalizing social processes and supporting management decisions. The use of fuzzy models allows for the formalization of the uncertainty, linguistic assessments, and subjective judgments inherent in social processes, which, in turn, increases the flexibility and accuracy of digital decision-making systems. This approach is consistent with the key objectives of the "Digital Kazakhstan" State Program, specifically the development of intelligent public administration information systems, decision-making based on data analysis, and effective monitoring of regional socioeconomic development. Thus, the formalization of social and socioeconomic processes based on fuzzy models and their integration into digital decision-support systems fully aligns with the strategic development goals of modern Kazakhstani society. This determines the scientific and practical significance of the dissertation research topic and enhances its relevance. Literature review. The study of social and socioeconomic processes is a key focus of classical sociology and modern management theory. The complexity, multifactorial nature, and dynamic nature of social processes require the development of universal methods for their formalization and modeling. The works of Émile Durkheim, Max Weber, Talcott Parsons, and Robert Merton examined the structure, functions, and patterns of change in social systems, laying the theoretical foundations for a systems analysis of social processes. These works comprehensively explored the determination of social change, institutional transformations, and the concept of social action. For a deeper understanding of the dynamic nature of social processes, Niklas Luhmann's theory of social systems and Jürgen Habermas's theory of communicative action are essential. These scholars view social processes as a system of information exchange, communication, and feedback, demonstrating that the quality of management decisions depends largely on the structure of the information. In this context, modeling social processes is an important tool for improving management effectiveness. In international scientific literature, issues of formalizing socioeconomic processes and decision-making are closely linked to multicriteria analysis and uncertainty theory. The theory of fuzzy sets, proposed by Lotfi Zadeh, pioneered a new approach to formalizing uncertain and qualitative information. These ideas were subsequently developed in the works of Howard Rife, Arnold Kofman, John Kluttz, and Richard Bellman, who laid the theoretical and applied foundations for the application of fuzzy logic to management and decision-making problems. In the field of social and regional development assessment, international researchers widely employ fuzzy multicriteria decision-making methods (Fuzzy AHP, Fuzzy TOPSIS, VIKOR, DEMATEL). For example, Thomas Saaty proposed the Analytic Hierarchy Process (AHP), which in subsequent studies has been adapted to fuzzy environments and is used for prioritizing social policy and comparative assessment of regional development. In these studies, the consideration of fuzzy relationships between social indicators is considered a key advantage of fuzzy models. The theory of fuzzy decision making and its application to socio-economic systems has been extensively developed in the works of scholars in CIS countries. S. A. Orlovsky, A. N. Melikhov, V. B. Borisov, and V. B. Kuzmin systematically examine the comparison of fuzzy alternatives, the aggregation of expert information, and management decision-making under uncertainty. The authors substantiate the limitations of traditional quantitative methods in describing social processes and demonstrate the methodological advantages of fuzzy logic in formalizing qualitative assessments. In Russian and CIS studies, the use of fuzzy models to assess socio-economic development indicators is considered an effective tool for substantiating regional policy. For example, it is proposed to use systems of fuzzy indicators to assess regional quality of life, the level of social infrastructure, and the well-being of the population. These studies emphasize that incorporating expert opinions improves the accuracy of management decisions. In the research of Kazakhstani scholars, issues of socio-economic development, regional policy, and quality of life assessment are considered in close connection with state strategic programs. Domestic studies analyze the development of social infrastructure, interregional inequality, social well-being, and management effectiveness. In recent years, concepts of digitalization, information systems, and data-driven management have increasingly become prominent in these studies. In Kazakhstan, a research field focused on the application of fuzzy logic and intelligent decision support systems is also emerging. Domestic authors demonstrate the effectiveness of fuzzy models in assessing social indicators, analyzing risks, and developing management decision support systems. These studies allow for the consideration of the specific features of social data in Kazakhstan. Overall, a literature review shows that traditional quantitative methods are insufficient for managing social processes, while approaches that consider uncertainty and qualitative information possess both scientific and practical validity. However, domestic and international studies have insufficiently systematized the integration of regional social processes, quality of life, and social infrastructure into a unified digital decision-making model. This gap defines the research focus of this dissertation and enhances its relevance. Purpose of the study. The aim of the study is to develop a decision support model based on fuzzy logic, designed for the effective management of socio-economic processes under conditions of uncertainty, taking into account regional development indicators and quality of life factors. Based on the purpose of the dissertation, the following tasks were set: 1. Systematize the key factors and indicators characterizing regional development and quality of life; 2. Develop a decision support model based on fuzzy logic under uncertainty; 3. Develop a hybrid decision support model for assessing regional development that integrates fuzzy logic with statistical and expert data; 4. Develop an information system for decision-making in the area of ​​regional socioeconomic development. The object of the study is the social and socio-economic processes formed at the regional level, as well as the system of indicators characterizing the quality of life of the population and the development of social infrastructure. The subject of the research is models and methods of decision support based on fuzzy logic, intended for the assessment and management of regional social and socio-economic processes under conditions of uncertainty, incompleteness, and qualitative nature of information. The research methods include comparative and structural analysis methods, mathematical statistics methods (correlation analysis, rank-based evaluation), expert assessment and survey methods, modeling based on fuzzy set theory and fuzzy logic, multi-criteria decision-making methods, and machine learning methods. Scientific novelty of the dissertation research: A fuzzy logic-based model for assessing social processes is proposed, taking into account the multidimensional, heterogeneous, and uncertain nature of social and socio-economic factors; A hybrid decision support model for regional development assessment is developed, integrating fuzzy logic with statistical and expert data. The methodological basis of the research is grounded in systemic, structural-functional, and multi-criteria approaches that allow for accounting for the multidimensionality and heterogeneity of social factors; during the study, decision-making models in social processes are developed based on the integration of qualitative and quantitative information. The scientific basis of the research comprises fundamental and applied works of domestic, CIS, and foreign scholars in the fields of social process theory, theory of management of social and socio-economic systems, decision-making theory under uncertainty, fuzzy set theory and fuzzy logic, as well as multi-criteria decision-making methods. The research methodology is based on the step-by-step implementation of decision-making tasks in social processes. Using expert assessments and statistical data, linguistic variables and membership functions were constructed, and a fuzzy logic-based decision-making model was developed. The proposed model was tested on real social data, and the obtained results were analyzed and compared with traditional evaluation methods. Based on the research results, methodological recommendations were developed to support managerial decision-making in social processes. Main provisions submitted for defense: A fuzzy logic-based model for assessing social processes that takes into account the multidimensional, heterogeneous, and uncertain nature of social and socio-economic factors; A hybrid decision support model for regional development assessment, integrating fuzzy logic with statistical and expert data; An information system for supporting decision-making in social processes. The theoretical significance of the dissertation is determined by its contribution to the development of decision-making theory based on fuzzy logic in addressing problems of analysis and management of social processes under conditions of uncertainty, incomplete, and qualitative information. The obtained results expand the theoretical foundations for the formalization and systematization of social and socio-economic factors, taking into account their multidimensionality and heterogeneity. The proposed approach enables the integration of systemic, structural-functional, and multi-criteria theories of social process modeling with the apparatus of fuzzy logic, thereby deepening the methodological foundations of decision-making models in the social sphere. The resulting theoretical conclusions may serve as a basis for further scientific research in the study, assessment, and management of social processes. This text is actually theoretical significance, not practical. Here is the correct English translation while keeping your meaning intact: The practical significance of the research is determined by the development and application potential of fuzzy logic-based decision-making approaches for solving problems of analysis and management of social processes under conditions of uncertainty, incomplete, and qualitative information. The results of the study contribute to the formalization and systematization of social and socio-economic factors, taking into account their multidimensionality and heterogeneity, and can be used in applied decision support systems. The proposed approach enables the integration of systemic, structural-functional, and multi-criteria models of social process analysis with fuzzy logic methods, which enhances the practical effectiveness of decision-making tools in the social sphere. The obtained results can serve as a foundation for developing applied systems and tools for supporting managerial decision-making in the assessment and management of social processes. Software. During the dissertation research, software for an information-analytical system based on fuzzy logic was developed, intended to support managerial decision-making in social processes. The developed software system ensures the integration of social and socio-economic data, expert assessments, and multi-criteria analysis methods within a unified environment. The software implements the functionality of formalizing factors influencing social processes, forming linguistic variables and membership functions, as well as implementing fuzzy logic-based decision-making models. The system includes algorithms for processing qualitative and quantitative information, assessing the relative importance of factors, and performing multi-criteria analysis of alternative managerial decisions. The software module provides input and storage of social indicators, processing of expert evaluations, automatic generation of a fuzzy rule base, calculation of alternative priorities, and evaluation of social process management scenarios. The user interface is designed to be clear and convenient for specialists in public and regional administration. Implementation of Results. The results of the dissertation research have been successfully implemented within the framework of solving problems of analysis and management of social processes at the regional level. The developed fuzzy logic-based decision support model was used as an information system that enables comprehensive assessment of social and socio-economic factors, taking into account their interrelations and providing justification for managerial decisions. The proposed model considers indicators of social development, quality of life factors, and infrastructure parameters as a unified system, which makes it possible to evaluate alternative scenarios for managing social processes. During implementation, a systemic approach was applied, based on the formation of a hierarchical structure of interrelated social factors, which ensured the quantitative assessment of their relative importance and the forecasting of possible consequences of managerial decisions. In addition, the formalization of qualitative characteristics and their integration with quantitative indicators was ensured, thereby increasing the validity of decisions made in the management of social processes. The practical application of the research results confirmed the high efficiency of the proposed fuzzy model under real social data conditions and its adaptability to the specifics of regional social development. The main results of the dissertation have been implemented in the practical activities of the Public Foundation “Sustainable Development of the Regional Economy,” confirming their applicability in the field of analysis and management of social processes. Approbation of the dissertation results. The main results of the dissertation research were presented at the following international conferences: – Application of a hybrid model for studying the impact of socio-economic factors on regional development / IX International Scientific Conference “Informatics and Applied Mathematics”, dedicated to the 90th anniversary of Al-Farabi Kazakh National University. Discussion and implementation of the research results: 2 articles have been published in journals indexed in the Scopus and Web of Science databases. Application of a hybrid model to study the influence of socio-economic factors on regional development //Bulletin of Electrical Engineering and Informatics. – 2026. – Т. 15 (59 th percentile). A Reproducible Hybrid Architecture of Fuzzy Logic and XGBoost for Explainable Tabular Classification of Territorial Vulnerability//Computers. -2026. (84 th percentile). 4 articles have been published in journals included in the list of scientific publications recommended by the Committee for Quality Assurance in the Sphere of Science and Higher Education of the Ministry of Science and Higher Education of the Republic of Kazakhstan. Исследование влияния социально-экономических факторов на развитие региона с использованием гибридной модели // Вестник КазАТК. – 2025. – Т. 137, №2. – С. 195-208. Аймақтық әлеуметтік процестерге әсер ететін факторларды бағалау үшін бұлдыр модельдерді практикалық қолдану бойынша ұсыныстар // Вестник КазАТК. – 2024. – Т. 135, №6. – С. 203-213. Аймақты дамытудың әлеуметтік процестерін бағалау үшін шешімдер қабылдаудың бұлдыр модельдері: аймақты дамытудың әлеуметтік процестерін бағалау үшін шешімдер қабылдаудың бұлдыр модельдері // Известия НАН РК. Серия физико-математическая. – 2024. – №2. – С. 69-84. Әлеуметтік процестерде шешімдер қабылдаудың бұлдыр модельдерін енгізу мәселелері // Physico-mathematical series. – 2025. – №1. – Р. 78-92. The act on the implementation of the results of the research work dated 09.01.2026 is presented in Appendix A. Information on the certificate entered into the State Register of Rights to Copyright Objects (Appendix B): “Hybrid system for assessing the impact of socio-economic factors on regional processes based on correlation analysis, PCA, and fuzzy inference.” Certificate of registration in the State Register of Rights to Copyright Objects No. 66710, dated January 27, 2026. Structure and scope of the dissertation. The dissertation is written in the Kazakh language and consists of an introduction, three chapters, a conclusion, a list of references, and appendices. The first chapter, examines the theoretical foundations of social and socio-economic factors characterizing social processes, analyzing their multifactorial nature, heterogeneity, and features under conditions of uncertainty. The issues of formalization of social processes and the necessity of applying fuzzy approaches in their modeling are substantiated. In the second chapter, issues of assessing regional social development and the quality of life of the population are considered. The main factors affecting quality of life are systematized, their interrelations with indicators of social infrastructure are analyzed, and methods of comprehensive factor assessment are described. In the third chapter, the development and practical application of a fuzzy logic-based model designed to solve decision-making problems in social processes under conditions of uncertainty are considered. The structure of the proposed model, the methods used, as well as the analysis and evaluation of the obtained results are presented. Acknowledgements. The author expresses sincere gratitude to the scientific supervisor — Associate Professor of the Department of Information Systems at L.N. Gumilyov Eurasian National University, Head of the Department, Mukhanova Ayagoz Asanbekovna, for the interesting tasks posed during the research and the valuable recommendations necessary for their solution. The author also expresses sincere gratitude to the foreign scientific consultant, PhD, Dean and Professor of the School of Science and Engineering at Al Akhawayn University (Ifrane, Kingdom of Morocco), Salah Al-Majid, for his interest in the work, professional consultations, and substantive remarks that contributed to deepening the scientific results and improving the quality of the research. The author also extends appreciation to the members of the scientific seminar of the L.N. Gumilyov Eurasian National University for their participation in the discussion of the research results and constructive suggestions that contributed to improving the quality of the work.

Dissertation

List of Scientific Works

Consultant's Review

Foreign Consultant's Review

Conclusion of the Research Ethics Committee