Defense of the dissertation of Tynykulova Assemgul for the degree of Doctor of Philosophy (PhD) in the educational program «8D06103 - Information systems»
L.N. Gumilyov Eurasian National University, a dissertation defense for the degree of Doctor of Philosophy (PhD) by Tynykulova Assemgul on the topic «Information system for optimal use of land resources in the (Ayyrtau district of North Kazakhstan region)» in 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 russian
Official reviewers:
Orken Zhumazhanovich Mamyrbayev - PhD, Professor, Deputy Director for Science at the RSE "Institute of Information and Computational Technologies" of the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Almaty, Republic of Kazakhstan).
Nurbapa Otanovich Mekebayev - PhD, Associate Professor of the Department of Informatics, Kazakh National Women's Pedagogical University (Almaty, Republic of Kazakhstan);
Temporary members of the Dissertation Council:
Grif Mikhail - Doctor of Technical Sciences, Professor at the Faculty of Automation and Computer Engineering, Novosibirsk State Technical University (Novosibirsk, Russian Federation);
Kongyrbayev Nurbek - Doctor of Philosophy (PhD), Associate Professor, Head of the educational program «Computer Science» Korkyt Ata Kyzylorda University (Kyzylorda Kazakhstan);
Yerimbetova Aigerim - PhD, Candidate of Technical Sciences, Associate Professor, Leading Researcher at the Institute of Information and Computational Technologies of the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Almaty, Republic of Kazakhstan).
Scientific consultants:
Mukhanova Ayagoz - PhD, Associate Professor of the Department of Information Systems, L.N. Gumilyov Eurasian National University (Astana, Republic of Kazakhstan);
Faddeenkov Andrey - Candidate of Technical Sciences, Associate Professor of the Department of Information Systems and Technologies, Zapolyarny State University named after N.M. Fedorovsky (Norilsk, Russian Federation).
The defense will take place on June 20, 2025, at 03:00 PM in the Dissertation Council for the training direction «8D061 - Information and communication technologies» in the educational program «8D06103 - Information systems» of L.N. Gumilyov Eurasian National University. Conducting a meeting of the dissertation council in a mixed (offline and online) format.
Link: https://clck.ru/3M3o7B
Address: Astana city, Pushkin Street 11, Educational Building No. 2, Room 222.
Abstract (English): the dissertation work of Tynykulova Assemgul Serguzhaevna "Information system for optimal use of land resources in the (Ayyrtau district of North Kazakhstan region)", submitted for the degree of Doctor of Philosophy (PhD) in the educational program "8D06103 - Information Systems". Relevance of the research topic. Rational use of land resources is one of the key tasks of sustainable agricultural development, especially in the context of a changing climate, soil degradation and economic challenges. The Ayyrtau district of the North Kazakhstan region has significant potential for agricultural production, but its effectiveness is significantly limited by a number of factors, including insufficient digitalization of land use management processes, soil degradation, suboptimal crop rotation schemes and a lack of systematized data for management decision-making. In today's environment, when the agro-industrial complex is faced with the task of increasing productivity and environmental sustainability, the use of digital technologies and intelligent land management systems plays an important role. One of the key problems of the region is the lack of reliable information on the state of soils, the level of moisture, the dynamics of yields and the impact of climate change. As a result, farms and agricultural enterprises face difficulties in planning agrotechnical measures, which leads to irrational use of land, increased costs and a decrease in the profitability of production. The introduction of an information system based on the use of geoinformation technologies (GIS) [1], Big Data technologies [2] and artificial intelligence (AI) methods [3] will automate the processes of collecting [4], analyzing and forecasting the state of agricultural land [5], ensuring effective decision-making [6, 7]. At the international level, similar information systems have already proven their effectiveness, especially in countries with a developed agricultural sector, such as the United States [8], Germany [9], China [10] and Canada [11]. The use of such technologies can significantly increase yields, reduce losses associated with adverse weather conditions, optimize fertilizer application and minimize irrigation costs. In Kazakhstan, the active introduction of digital solutions in the agro-industrial complex is supported by government programs aimed at the development of "smart agriculture" [12] and the digitalization of resource management [13]. The relevance of this work is due to the need to increase the economic efficiency of agriculture, reduce the risks associated with the variability of climatic conditions and non-optimal use of land, as well as the introduction of innovative solutions that automate the processes of analysis and forecasting. In the context of limited land resources and increasing demand for food, sustainable management of agricultural land that balances productivity and environmental sustainability is of particular importance. The development and implementation of an information system for the optimal use of land resources in the Ayyrtau district will create a single digital tool that combines data on soil characteristics, moisture levels, yield dynamics, crop rotation schemes and other critical parameters. This will provide agricultural enterprises with access to up-to-date analytical information, increase the accuracy of forecasts and optimize the use of natural resources. In addition, the system will contribute to reducing the negative impact of agriculture on the environment by preventing soil degradation, excessive use of chemical fertilizers and rational allocation of water resources. Thus, the development of an information system for optimal land management in the Ayyrtau district is a relevant and in-demand scientific research that has both theoretical and practical significance. The introduction of digital technologies and intelligent management systems in the agricultural sector will increase the competitiveness of agriculture, minimize risks associated with external and internal factors, and ensure the sustainable development of the agro-industrial complex of Kazakhstan. The purpose of the dissertation research: Development of an information system for the optimal use of land resources of the Aiyrtau district, based on modern digital technologies and methods of data analysis. Objectives of the study: 1. Review of scientific research on the optimal use of land resources. 2. Create a classification model for crop selection. 3. Creation and implementation of an information system for land management, including databases, analytical modules and user interface. 4. Evaluation of the effectiveness of the developed classification model. Research methods: Data analysis and geoinformation technologies, machine learning methods, Big Data technologies, multi-criteria optimization methods. Description of the main results of the study: 1. An ensemble classification model has been developed for the selection of optimal crops. 2. A model for forecasting the optimal distribution of land resources has been developed. Substantiation of the novelty and importance of the results obtained: The research methodology is based on an integrated approach to the analysis and optimization of the use of land resources in the Ayyrtau district using modern digital technologies, mathematical modeling and artificial intelligence methods. The work includes several stages that combine data collection, processing and analysis, the development of optimization algorithms, the creation of an information system and its experimental verification. An integrated approach to optimizing the use of land resources in the Ayyrtau district has been developed, based on the use of machine learning methods, multi-criteria optimization and geographic information systems (GIS). The proposed methodology makes it possible to increase the accuracy of forecasting land productivity, reduce uncertainty in the management of the agro-industrial complex and ensure the rational use of agricultural land. The methodological basis of this study is based on an integrated approach to the analysis and optimization of land resources use using modern digital technologies, mathematical modeling and machine learning methods. The basis of the study is the application of machine learning and analytical methods for optimal management of agricultural land. In particular, the methods of gradient boosting [26], ensemble algorithms (XGBoost [27], Random Forest), as well as interpretive models (SHAP, AHP) are used to identify patterns in the data and improve the accuracy of yield forecasting. These approaches enable automated decision-making, which is especially important for the agricultural sector in an uncertain environment. Compliance with the directions of scientific development or state programs: The research work is in line with the state program for the development of the agro-industrial complex of the Republic of Kazakhstan for 2021-2025, which is aimed at introducing digital technologies in the field of agriculture and improving the quality of public services. In addition, the research is relevant to the areas of scientific development in the field of agricultural technologies in the world, especially in terms of remote monitoring of the state of crops in agriculture, early detection of pests and diseases, and improvement of digital monitoring systems. to increase productivity. The results of this work correspond to the directions of development of science on digitalization, automation and improving the efficiency of agriculture. A description of the applicant's contribution to the preparation of each publication. The results of the dissertation research are reflected in 7 scientific articles, where the applicant is the first author: Articles in international peer-reviewed scientific journals Web of Science Core Collection, Scopus -1. A. Tynykulova., A.Mukhanova, A. Mukhomedyarova, Zh. Alimova, N.Tasbolatuly, U. Smailova, M.Kaldarova, M.Tynykulov Integrating numerical methods and machine learning to optimize agricultural land use. International Journal of Electrical and Computer Engineering (IJECE) Vol. 14, No. 5, October 2024, pp. 5420~5429 ISSN: 2088-8708, DOI: 10.11591/ijece.v14i5.pp5420-5429. The article presents a study aimed at developing an integrated methodology for forecasting and optimizing the use of agricultural land using numerical methods and machine learning algorithms. The main goal of the work is to increase the productivity and economic efficiency of agrocenoses through an accurate analysis of factors affecting yields and profitability. The study used methods to reduce the dimensionality of data, including principal component analysis (PCA) and factor analysis (FA), which made it possible to reduce the amount of information and identify the most significant variables. A simplex method was used to allocate resources. Forecasting the yield and productivity of farmland was carried out using three different algorithms: LightGBM, XGBoost and SVM. LightGBM showed the highest accuracy (99.98%), XGBoost also gave reliable results (95.99%), while SVM showed lower accuracy (43.65%). Analytical approaches combined with the capabilities of artificial intelligence can be effectively used to create predictive systems in the agricultural sector. The results of the study open up prospects for the implementation of such models in digital decision-support platforms, which can significantly facilitate the work of farmers, agronomists and agricultural managers. II. In publications recommended by the Committee for Quality Assurance in the Field of Science and Higher Education of the Ministry of Science and Higher Education of the Republic of Kazakhstan - 5. Tynykulova A.S., Mukhanova A.A. Soltústik Qazaqstan oblysy Ayyrtaý aýdanynyń mysalynda jer resurstaryn ońtaıly paıdalaný úshin aqparattyq júıeni qurý algorımıtmi. QR UǴA Habarlary. Physics-Informatics Series, No1 (349), 2024 С. 356-367 ISSN 1991-346X https://doi.org/10.32014/2024.2518-1726.261. Tynykulova A.S., Mukhanova A.A., Faddeenkov A.V. Analysis and Optimization of Risk Management in Conditions of Uncertainty: Modern Methods and Technologies Izvestiya NAS RK. Series of Physics and Informatics, No2 (350), 2024 pp. 325-335 ISSN 1991-346X https://doi.org/10.32014/2024.2518-1726.286. Tynykulova A., Mukhanova A. Development and application of an integrated information model for optimizing land use and forecasting yields in agricultural production. KazTBU KHABARSHYSY - VESTNIK KazUTB series Information, Communication and Chemical Technologies No2-23 (2024) p 135-145 https://doi.org/10.58805/kazutb.v.2.23-463. Tynykulova A.S., Mukhanova A.A. Ontology modeldi ázirleý jáne modeldeý - aýyl sharýashylyǵynda jerdi tiimdi ońtaılandyrý tásili retinde QazKKA Khabarshysy No 4 (133), 2024 Vestnik KazATK No 4 (133), 2024, Series Automation, Telemechanics, Communication, Computer Science, p 201-210 DOI 10.52167/1609-1817-2024-133-4-201-210. Tynykulova A.S., Mukhanova A.A. Jer resurstaryn ońtaılandyrýdyń aqparattyq júıesin qurý máseleleri jáne ádisterdi taldaý. QazKKA Khabarshysy No 3 (132), 2024, Vestnik KazATK Series Automation, Telemechanics, Communication, Computer Science No 3 (132), 2024 pp. 467-477. https://DOI 10.52167/1609-1817-2024-132-3-467-477. In his works, the author considered the development of a conceptual information model for optimizing land use and forecasting yields in agriculture. In the course of his work, new algorithms for processing big data were developed, modern programming technologies (PHP, JavaScript, MySQL) were used to implement the model. The author contributed to the design of the database structure and the creation of information flows for modeling land use. The author also participated in the study of modern methods of analysis and optimization of risk management in conditions of uncertainty. Methods of multi-criteria optimization, machine learning and Monte Carlo modeling were studied and applied to improve the sustainability of agricultural systems, and contributed to the development of adaptive risk management strategies taking into account climatic and economic factors. III. In the collections of international scientific and practical conferences - 1. Tynykulova A.S., Faddeenkov A.V. Factors Influencing the Optimality of Land Resources / Collection of Articles of the International Scientific and Practical Conference "AIU-2024: Synergy of Education, Science and Artificial Intelligence: From Idea to Practice" No4 (5) 2024 P. 54-63. Thesis structure. The structure of the thesis corresponds to the purpose and objectives of the study and consists of an introduction, three main sections: each section includes three subsections, conclusions, and a list of sources used. The total volume of the dissertation is 132 pages, the number of sources used is 85, the number of references to regulatory documents is 41, the author's certificate for the computer program "Crop Programming" (Appendix A), the Act of Practical Application and Implementation (Appendix B).
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