Fuzzy Logic for Yield Prediction: Enhancing Decision-Making in Agricultural Economics Rahib Imamguluyev, Agil Gurbanov, Ayatulla Jabbarov, Shalala Hasanova, Gunay Rasulova, Sevinj Karimova, Jeyran Khalilova, Reyhan Azizova, Lamiya Tahirova Agris on Line Papers in Economics and Informatics, 2026 Accurate yield prediction is essential for optimizing decision-making in agricultural economics, enabling stakeholders to manage resources efficiently and respond to market demands. Traditional yield prediction models often struggle to handle the uncertainties and complexities inherent in agricultural systems, such as weather variability, soil conditions, and crop characteristics. This study introduces a fuzzy logic-based approach to yield prediction, offering a more flexible and robust method for addressing these uncertainties. By utilizing fuzzy sets and rules, the proposed model captures the intricate relationships between multiple factors influencing crop yield. The research demonstrates how fuzzy logic can enhance the accuracy and reliability of yield predictions, providing valuable insights for farmers, policymakers, and agricultural economists. Results indicate that this approach significantly improves decision-making processes in agricultural planning and risk management, making it a valuable tool for sustainable agricultural practices.
Decision Making Under Uncertainty: A Z-Number-Based Regret Principle Ramiz Alekperov, Vugar Salahli, Rahib Imamguluyev Mathematics, 2025 Decision-making theory has developed over many decades at the intersection of economics, mathematics, psychology, and engineering. Its classical foundations include Bernoulli’s expected utility theory, von Neumann and Morgenstern’s rational choice theory, and the criteria proposed by Savage, Wald, Hurwicz, and others. However, in real-world contexts, decisions are made under uncertainty, incompleteness, and unreliability of information, which classical approaches do not adequately address. To overcome these limitations, modern multi-criteria decision-making methods such as Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), VlseKriterijumska Optimizacija I Kompromisno Resenje (Compromise solution approach) (VIKOR), and ELimination Et Choix Traduisant la REalité (Elimination and Choice Expressing Reality) (ELECTRE), as well as their fuzzy and Z-number extensions, are widely applied to the modeling and evaluation of complex systems. These Z-number extensions are based on the concept of Z-numbers introduced by Lotfi Zadeh in 2011 to formalize higher-order uncertainty. This study introduces the Z-Regret principle, which extends Savage’s regret criterion through the use of Z-numbers. Supported by Rafik Aliev’s mathematical justifications concerning arithmetic operations on Z-numbers, the model evaluates regret not only as a loss relative to the best alternative but also by incorporating the degree of confidence and reliability of this evaluation. Calculations for the selection of digital advertising platforms in terms of performance assessment under various scenarios demonstrate that the Z-Regret principle enables more stable and well-founded decision-making under uncertainty.
Integrating Fuzzy Logic with Deep Learning: A New Approach to Explainable Artificial Intelligence Rahib Imamguluyev 6th International Conference on Mobile Computing and Sustainable Informatics Icmcsi 2025 Proceedings, 2025 The rapid progress in artificial intelligence (AI) has led to the development of robust deep learning models, yet their black box nature presents major challenges regarding interpretability and transparency. This article presents a novel method for explainable artificial intelligence (XAI) that merges Fuzzy Logic with deep learning. Fuzzy logic is renowned for its capability to manage uncertainty and facilitate approximate reasoning, providing a clear framework that enhances the decision-making capabilities of deep learning models. By integrating systems grounded in fuzzy rules, our goal is to boost the interpretability of deep learning models while maintaining their predictive performance. The proposed strategy connects human-understandable logic with the intricate calculations of neural networks, shedding light on the internal mechanisms of artificial intelligence systems. We validate the effectiveness of this combined approach through various case studies and experiments, showcasing enhanced transparency and reliability of the models. This fusion of Fuzzy Logic with deep learning adds to the expanding domain of XAI and holds promise for broader applications where explainability is crucial, such as in healthcare, finance, and autonomous systems.
A Fuzzy Inference System for Addressing Contemporary Challenges and Elevating Digital Marketing in the Culinary Tourism Industry. R Imamguluyev, M Gurbanova, V Heydarov, L Atakishiyeva, S Guluzada, ... Journal of Multiple-Valued Logic & Soft Computing 46 , 2025 2025
Decision Making Under Uncertainty: A Z-Number-Based Regret Principle R Alekperov, V Salahli, R Imamguluyev Mathematics 13 (22), 3579 , 2025 2025 Citations: 2
Fuzzy Logic for Yield Prediction: Enhancing Decision-Making in Agricultural Economics R Imamguluyev, A Gurbanov, A Jabbarov, S Hasanova, G Rasulova, ... AGRIS on-line Papers in Economics and Informatics 17 (3), 27-36 , 2025 2025 Citations: 2
A Fuzzy Logic-Based Framework for Pragmatic Analysis of Brexit-Related Discourse in Contemporary British Media Texts R Imamguluyev, T Alizade, T Imanova, A Osmanova, A Mamedova, ... International Conference on Intelligent and Fuzzy Systems, 94-102 , 2025 2025
Applying Fuzzy Logic to Institutional Performance Evaluation in Universities G Bayramova, R Imamguluyev, E Bayramov International Conference on Intelligent and Fuzzy Systems, 673-680 , 2025 2025
A Fuzzy Logic-Based Framework for Pragmatic Analysis of Brexit-Related Discourse in Contemporary British Media Texts S Musayeva, S Islamova Intelligent and Fuzzy Systems: Artificial Intelligence in Human-Centric … , 2025 2025
Fuzzy Logic-Driven AI: Bridging Human-Centric Intelligence and Autonomous Networks for Next-Gen Communication Systems R Imamguluyev, U Poladova, G Azizova, S Hajizada, A Mammadova, ... International Conference on Intelligent and Fuzzy Systems, 808-815 , 2025 2025
Revolutionizing Green Energy Systems: A Fuzzy Logic-Based Approach for Optimized Resource Management R Imamguluyev International Conference on Intelligent and Fuzzy Systems, 799-807 , 2025 2025
Adaptive Resource Allocation in 6G Networks Using Fuzzy Logic F Sadikoglu, R Imamguluyev International Conference on Intelligent and Fuzzy Systems, 816-823 , 2025 2025
Fuzzy Logic for Modeling Climate Changes: Overcoming Uncertainty in Environmental Forecasts R Imamguluyev, S Hajizada, S Badalova, A Mammadova, S Abdullayeva, ... International Conference on Intelligent and Fuzzy Systems, 278-285 , 2025 2025
Fuzzy Logic for Modeling Climate Changes: Overcoming Uncertainty in Environmental R Imamguluyev, S Hajizada, S Badalova, A Mammadova, S Abdullayeva, ... Intelligent and Fuzzy Systems: Artificial Intelligence in Human-Centric … , 2025 2025
Fuzzy Logic-Enhanced Sentiment Analysis: A Multilingual and Multimodal Perspective for Social Media Insights R Imamguluyev International Conference on Intelligent and Fuzzy Systems, 544-552 , 2025 2025
Fuzzy Logic-Driven Privacy-Preserving Big Data Analytics: Enhancing Intelligent Information Systems R Imamguluyev, T Imanova, P Hasanova, U Poladova, G Azizova International Conference on Intelligent and Fuzzy Systems, 327-334 , 2025 2025
Detection and Prevention of Cyber Attacks Based on Fuzzy Logic and Deep Learning R Imamguluyev International Conference on Intelligent and Fuzzy Systems, 402-409 , 2025 2025
Integrating Fuzzy Logic into Green Pedagogy: An Intelligent Framework for English Language Teaching and Environmental Awareness R Imamguluyev, T Imanova, A Soltanova, N Orujova, T Atakishiyeva, ... International Conference on Intelligent and Fuzzy Systems, 181-188 , 2025 2025
Adaptive Emotional Intelligence in Human-AI Collaboration: A Fuzzy Logic Perspective F Sadikoglu, R Imamguluyev International Conference on Intelligent and Fuzzy Systems, 565-572 , 2025 2025
The Role of Fuzzy Logic in the Digital Transformation of Economics: Innovative Analysis and Strategies R Imamguluyev, A Panahov, A Jabbarov, A Hajiyev, K Aghayeva International Conference on Intelligent and Fuzzy Systems, 676-683 , 2025 2025 Citations: 1
Fuzzy Logic in Financial Forecasting: Improving Risk Assessment in Volatile Markets R Imamguluyev, G Nasrullayeva, S Abdullayeva, S Hajizada, S Badalova, ... International Conference on Intelligent and Fuzzy Systems, 283-290 , 2025 2025
Evaluating University-National Student Organization Cooperation: A Fuzzy Logic Approach E Bayramov, R Imamguluyev, G Bayramova International Conference on Intelligent and Fuzzy Systems, 105-112 , 2025 2025
Integrating Fuzzy Logic into Green Pedagogy: An Intelligent Framework for English Language N Orujova, T Atakishiyeva, Z Yusubova Intelligent and Fuzzy Systems: Artificial Intelligence in Human-Centric … , 2025 2025
MOST CITED SCHOLAR PUBLICATIONS
The Rise of GPT-3: Implications for Natural Language Processing and Beyond R Imamguluyev Journal homepage: www. ijrpr. com ISSN 2582, 7421 , 2023 2023 Citations: 48
Unlocking energy efficiency: harnessing fuzzy logic control for lighting systems R Imamguluyev, T Imanova, P Hasanova, A Mammadova, S Hajizada Procedia Computer Science 230, 574-583 , 2023 2023 Citations: 34
Prospects for the development of transport logistics and a fuzzy logic model of the strategic goals of the logistics system of Azerbaijan R Imamguluyev, A Suleymanov International Conference on Intelligent and Fuzzy Systems, 93-100 , 2022 2022 Citations: 29
Staff selection with a fuzzy analytical hierarchy process in the tourism sector A Valiyev, R Imamguluyev, I Gahramanov International Conference on Theory and Application of Soft Computing … , 2021 2021 Citations: 29
Application of Fuzzy Logic Apparatus to Solve the Problem of Spatial Selection in Architectural-Design Projects R Imamguluyev, N Umarova Intelligent and Fuzzy Techniques for Emerging Conditions and Digital … , 2022 2022 Citations: 28
Evaluation of the effectiveness of integration processes in production enterprises based on the fuzzy logic model R Imamguluyev, T Suleymanli, N Umarova International Conference on Theory and Applications of Fuzzy Systems and … , 2020 2020 Citations: 28
Ai-powered educational tools: Transforming learning in the digital era R Imamguluyev, P Hasanova, T Imanova, A Mammadova, S Hajizada, ... International Research Journal of Modernization in Engineering Technology … , 2024 2024 Citations: 25
Fuzzy Logic Control for Color-Tunable Lighting Systems R Imamguluyev International Conference on Intelligent and Fuzzy Systems, 744-750 , 2023 2023 Citations: 25
Determination of Correct Lighting Based on Fuzzy Logic Model to Reduce Electricity in the Workplace R Imamguluyev International Conference on Eurasian Economies 12 , 2020 2020 Citations: 25
Enhancing Node Selection in Blockchain-Enabled Edge Internet of Things (IoT): A Fuzzy Logic Approach for Improved Performance R Imamguluyev, A Hasanov, R Mikayilova 2023 7th International Conference on I-SMAC (IoT in Social, Mobile … , 2023 2023 Citations: 24
Application of fuzzy logic model for optimal solution of light reflection value in lighting calculations T Abdullayev, R Imamguluyev, N Umarova 11th International Conference on Theory and Application of Soft Computing … , 2022 2022 Citations: 24
Navigating the ethics of the metaverse: a fuzzy logic approach to decision-making R Imamguluyev, N Umarova, R Mikayilova International Conference on Intelligent and Fuzzy Systems, 53-60 , 2023 2023 Citations: 23
Improving the Mechanism of Using the Price Factor in the Effective Regulation of Agricultural Production on the Basis of Fuzzy Logic R Imamguluyev, E Balakishiyev, N Agakishiev International Journal of Innovative Technologies in Economy 5, 32 , 2020 2020 Citations: 23
Application of fuzzy logic model for daylight evaluation in computer aided interior design areas A Valiyev, R Imamguluyev, G Ilkin International Conference on Theory and Applications of Fuzzy Systems and … , 2020 2020 Citations: 23
Application of fuzzy logic model for correct lighting in computer aided interior design areas R Imamguluyev International Conference on Intelligent and Fuzzy Systems, 1644-1651 , 2020 2020 Citations: 23
Enhancing IoT efficiency: the role of fuzzy logic in smart decision making R Imamguluyev, J Nabiyeva, T Imanova, R Mikayilova, N Umarova, ... 2024 5th International Conference on Mobile Computing and Sustainable … , 2024 2024 Citations: 22
Application of fuzzy logic model to save energy in LED lighting systems in office spaces A Valiyev, R Imamguluyev World Conference Intelligent System for Industrial Automation, 357-364 , 2022 2022 Citations: 22
Application of a fuzzy logic model for optimal assessment of the maintenance factor affecting lighting in interior design R Imamguluyev, R Mikayilova, V Salahli Mobile Computing and Sustainable Informatics: Proceedings of ICMCSI 2022 … , 2022 2022 Citations: 22
Integrating fuzzy logic with deep learning: A new approach to explainable artificial intelligence R Imamguluyev 2025 6th International Conference on Mobile Computing and Sustainable … , 2025 2025 Citations: 20
Designing climate control with fuzzy logic for smart home systems A Valiyev, R Imamguluyev, R Mikayilova Mobile Computing and Sustainable Informatics: Proceedings of ICMCSI 2023 … , 2023 2023 Citations: 19
