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Grok-Based Temporal Fusion Transformer Framework for Multi-Horizon Coastal Flood Risk Forecasting and Strategic Adaptation Planning

Alexey MikhaylovFinancial Faculty, Financial University under the Government of the Russian Federation, Moscow 125167, Russia Department of Science, Baku Eurasian University, Baku AZ 1073, AzerbaijanSergey BarykinGraduate School of Service and Trade, Peter the Great St. Petersburg Polytechnic University, St. Petersburg 195251, RussiaDaria DinetsDepartment of Finance, Accounting, and Auditing, Peoples' Friendship University of Russia named after Patrice Lumumba, Moscow 125167, RussiaAkram OchilovDepartment of Economics, Karshi State University, Karshi 180119, UzbekistanAlfiya KuznetsovaDepartment of Economics, Bashkir State Agrarian University, Ufa 450001, RussiaJamshid TukhtabaevDepartment of Finance and Accounting, Graduate School of Business and Entrepreneurship under The Cabinet of Ministers of The Republic of Uzbekistan, Tashkent 100000, UzbekistanAslitdin NizamovBukhara Engineering Technological Institute, Bukhara 200100, UzbekistanNodira MurodovaDepartment of Regional Economics, Navoi State University, Navoi 210100, UzbekistanNasiba AshurovaDepartment of Economy & Management, Navoi State University of Mining and Technologies, Navoi 210100, UzbekistanTomonobu SenjyuDepartment of Electrical and Electronics Engineering, Faculty of Engineering, University of the Ryukyus, Okinawa 903-0213, JapanValery AbramovInstitute for Research of International Economic Relations, Financial University under the Government of the Russian Federation, Moscow 125167, RussiaN. B. A. YousifDepartment of Sociology, College of Humanities and Science, Ajman University, Ajman P.O. Box 346, United Arab Emirates Humanities and Social Sciences Research Centre (HSSRC), Ajman University, Ajman P.O. Box 346, United Arab Emirates

Research in Ecologyjournal2026

ABI

Аннотация

The optimized Grok algorithm can significantly improve the accuracy of time series analysis and understanding the dynamics of climate change. Fine-tuned Grok architecture can be used to monitor and analyze climate processes. The main aim is to analyze the Fine-tuned Grok architecture for research on climate change, world ecology, carbon dioxide growth, and carbon funds. The global challenges of climate change and ecological degradation demand innovative analytical approaches capable of processing vast, multivariate, and non-linear datasets. Concurrently, the global financial system, deeply intertwined with energy transitions and sustainable development, requires sophisticated tools for risk assessment and investment strategy in a changing world. Fine-tuned Grok architecture model helps to plan strategies for adaptation to climate change by calculating the optimal allocation of resources, taking into account risks and reducing losses. Due to its ability to respond quickly to new conditions, the system will be able to quickly adjust evacuation plans, deploy protective structures, and distribute assistance to affected regions. The use of artificial intelligence significantly expands the capabilities of the scientific community and authorities in monitoring, assessing, and managing climate change. The optimized Fine-tuned Grok architecture opens the way to a new level of informed decision-making about climate change and ensuring the safety of our future generations.

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Мавзулар

Tropical and Extratropical Cyclones Research Flood Risk Assessment and Management Geophysics and Gravity Measurements

Идентификаторлар

DOI: 10.30564/re.v8i1.12824

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