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Evolvement ofartificialintelligence andhybrid methods formodeling andoptimization incomplex systems Malsagov BekhanKetova FardianaMakienko Danila2025 год

Evolvement of artificial intelligence and hybrid methods for modeling and optimization in complex systems : доклад, тезисы доклада
доклад, тезисы доклада, статья из сборника материалов конференций

Дополнительные ссылки: eLibrary · Источник статьи
База данных: Каталог библиотеки СФУ
Библиографическое описание: Evolvement of artificial intelligence and hybrid methods for modeling and optimization in complex systems : доклад, тезисы доклада / B. B. Malsagov, F. F. Ketova, D. D. Makienko. - [S. l. : s. n.], 2025. - Текст : непосредственный // ITM Web of Conferences : III International Workshop / Hybrid Methods of Modeling and Optimization in Complex Systems (HMMOCS-III 2024) (2024 ; 02.12 - 04.12 ; Krasnoyarsk). - Krasnoyarsk, 2025. - P. 1004. - This work was supported by the Ministry of Science and Higher Education of the Russian Federation (Grant No.075-15-2022-1121). - DOI 10.1051/itmconf/20257201004.
Аннотация: Artificial intelligence (AI) has rapidly evolved to become an integral part of our daily lives, with its absence potentially causing significant disruptions. This paper examines the current trajectory of AI development and its projected impact on society in the near future. We explore the fundamental aspects of AI technology, its applications across various sectors, and the associated challenges and opportunities. The study also investigates the integration of hybrid methods for modeling and optimization in complex systems, highlighting their synergistic relationship with AI advancements. By combining analytical and data-driven approaches, these hybrid methods enhance AI's capabilities in addressing multifaceted problems across diverse domains. Our analysis encompasses the potential societal implications of AI, including job market transformations, ethical considerations, and the need for regulatory frameworks. Through this comprehensive examination, we aim to provide insights into the possible future states of AI technology and its far-reaching effects on human society.
Год издания: 2025
Авторы: Malsagov Bekhan , Ketova Fardiana , Makienko Danila
Издательство: Krasnoyarsk
Источник: ITM Web of Conferences
Номера страниц: 1004
Держатель оригинала документа: Kabardino-Balkarian State University, Kadyrov Chechen State University, Siberian Federal University
Мероприятие: Hybrid Methods of Modeling and Optimization in Complex Systems (HMMOCS-III 2024) (Krasnoyarsk, 2024 ; 02.12 - 04.12)
Количество экземпляров:
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