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1Academic Journal
Authors: Гэ Мэн, Университет финансов и экономики Цзянси, Meng Ge, Universitet finansov i ekonomiki Tsziansi
Contributors: This work is supported by the 2024 Annual Research Project of the Children's Artificial Intelligence Education Research Institute, China National Children's Center (Project No.: CNNCCYJY 2024010).
Source: Relevant Problems of Neurosensomotor Children's Development: Family and Environmental Supporting Factors; 12-19 ; Актуальные проблемы нейросенсомоторного развития детей: семейные и средовые поддерживающие факторы; 12-19
Subject Terms: музыкальная терапия, искусственный интеллект, artificial intelligence, теоретические основы, экспериментальный путь, music therapy, theoretical basis, experimental pathway
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Relation: info:eu-repo/semantics/altIdentifier/isbn/978-5-907830-73-8; https://phsreda.com/e-articles/10615/Action10615-112842.pdf; Artificial intelligence and generative music: will neural networks deprive musicians of work (2021) [Electronic resource]. – Access mode: https://www.techinsider.ru/technologies/724783-iskusstvennyy-intellekt-i-generativnaya-muzyka-lishat-li-neyroseti-raboty-muzykantov/ (date of application: 24.10.2023).; Haase-Rapoport K. (1990). Artificial intelligence. Radio and communications. Moscow.; Gorbacheva A. (2018). Artificial Intelligence and Contemporary Art: New Opportunities and Challenges. 13: 145–154.; Ignatiev A. (2022). Ethics in the field of artificial intelligence in the focus of interdisciplinary research and the development of national approaches. Moscow: MGIMO Publishing House.; Kuznetsov A. (2012). Functional representation of music and approaches to structural synthesis. Computer Science, Telecommunications and Management. 1: 11–20.; Morkovkin E. (2021). Artificial Intelligence as a Tool of Contemporary Art. Bulletin of Khakass State University. 2: 55–59.; Nagornaya L. (2020) Scientific achievements and artificial intelligence in the world of musical art. Culture and Education: scientific and informational journal of universities of Culture and Arts. 10: 32–43.; Ovchinnikov Y. (2022). Anthropological foundations of music-oriented health-saving technologies. Musical art and education. 10: 46–64. https://doi.org/10.31862/2309-1428-2022-10-2-46-64. EDN: JUGGKU; Palmov S. (2023). The use of artificial intelligence by music services. Applied Economic research. 1: 198–203. https://doi.org/10.47576/2949-1908_2023_1_198. EDN: LXDVZM; Peredelkina O. Neural Sonata: How artificial intelligence generates music [Electronic resource]. – Access mode: https://trends.rbc.ru/trends/industry/5f84b49e9a794729fefb4c88 (date of application: 25.10.2023).; Petrushkin V. (2019). Music therapy today: science, practice, education. AMPP, Moscow.; Razin A. (2019). Ethics of Artificial Intelligence. Philosophy and Society. 1: 57–73. EDN: YPCXWS; Shaip J. (2023). AI in the Music industry: The crucial Role of training data in machine learning models [Electronic resource]. – Access mode: https://ru.shaip.com/blog/training-data-for-music-ml-models/?ysclid=lo448l69q339791753 (date of application: 24.10.2023).; Shwars I. Can artificial intelligence create art? (2020) [Electronic resource]. – Access mode: https://habr.com/ru/companies/microsoft/articles/497308/ (date of application: 24.10.2023).; Solovyova D. (2021). How artificial intelligence composes music [Electronic resource]. – Access mode: https://lumos.art/music/ai-music/?ysclid=lo5m6vzone333843258 (date of application: 24.10.2023).; https://phsreda.com/article/112842/discussion_platform
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2Academic Journal
Subject Terms: Авторы БГТУ, БГТУ им. В. Г. Шухова, сверхпрочный бетон, Валерий Лесовик, строение пород, экспериментальный путь
File Description: application/pdf
Relation: http://dspace.bstu.ru/jspui/bitstream/123456789/1554/1/%d0%b4%d0%bb%d1%8f%20%d1%8d%d0%ba%d1%81%d1%82%d1%80%d0%b5%d0%bc%d0%b0%d0%bb%d1%8c%d0%bd%d1%8b%d1%85%20%d1%83%d1%81%d0%bb%d0%be%d0%b2%d0%b8%d0%b9.pdf; http://dspace.bstu.ru/jspui/handle/123456789/1554
Availability: http://dspace.bstu.ru/jspui/handle/123456789/1554
