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http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/7732| Назва: | Advances in machine learning for the innovation economy: in the shadow of war |
| Автори: | Danylchuk, Hanna B. Семеріков, Сергій Олексійович Данильчук, Ганна Борисівна |
| Ключові слова: | computational intelligence data science innovation economy artificial neural networks machine learning visualization |
| Дата публікації: | 28-сер-2023 |
| Бібліографічний опис: | Danylchuk H. B. Advances in machine learning for the innovation economy: in the shadow of war [Electronic resource] / Hanna B. Danylchuk, Serhiy O. Semerikov // Proceedings of the Selected and Revised Papers of 10th International Conference on Monitoring, Modeling & Management of Emergent Economy (M3E2-MLPEED 2022). Virtual Event, Kryvyi Rih, Ukraine, November 17-18, 2022 / edited by : Hanna B. Danylchuk, Serhiy O. Semerikov // CEUR Workshop Proceedings. – 2023. – Vol. 3465. – Pp. 1–25. – Access mode: https://ceur-ws.org/Vol-3465/paper00.pdf |
| Короткий огляд (реферат): | This preface introduces the selected and revised papers presented at the 10th International Conference on Monitoring, Modeling & Management of Emergent Economy (M3E2 2022), held online in Ukraine, on November 17-18, 2022. The conference aimed to bring together researchers, practitioners, and students from various fields to exchange ideas, share experiences, and discuss challenges and opportunities in applying computational intelligence and data science for the innovation economy. The innovation economy is a term that describes the emerging paradigm of economic development that is driven by knowledge, creativity, and innovation. It requires new approaches and methods for solving complex problems, discovering new opportunities, and creating value in various domains of science, business, and society. Computational intelligence and data science are two key disciplines that can provide such approaches and methods by exploiting the power of data, algorithms, models, and systems to enable intelligent decision making, learning, adaptation, optimization, and discovery. The papers in this proceedings cover a wide range of topics related to computational intelligence and data science for the innovation economy. They include theoretical foundations, novel techniques, and innovative applications. The papers were selected and revised based on the feedback from the program committee members and reviewers who ensured their high quality. We would like to thank all the authors who submitted their papers to M3E2 2022. We also appreciate the keynote speakers who shared their insights and visions on the current trends and future directions of computational intelligence and data science for the innovation economy. We acknowledge the support of our sponsors, partners, and organizers who made this conference possible despite the challenging circumstances caused by the ongoing war in Ukraine. Finally, we thank all the participants who attended the conference online and contributed to its success. |
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| URI (Уніфікований ідентифікатор ресурсу): | https://ceur-ws.org/Vol-3465/paper00.pdf http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/7732 https://doi.org/10.31812/123456789/7732 |
| ISSN: | 1613-0073 |
| Розташовується у зібраннях: | Кафедра інформатики та прикладної математики |
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