Advances in machine learning for the innovation economy: in the shadow of war

Author:

Danylchuk Hanna B.,Semerikov Serhiy O.

Abstract

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 committe 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.

Publisher

Криворізький державний педагогічний університет

Reference52 articles.

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3. [3] A. E. Kiv, V. N. Soloviev, S. O. Semerikov, H. B. Danylchuk, L. O. Kibalnyk, A. V. Matviychu A. M. Striuk, Machine learning for prediction of emergent economy dynamics III, in: A. E. Kiv, V. N. Soloviev, S. O. Semerikov (Eds.), Proceedings of the Selected and Revised Papers of 9th International Conference on Monitoring, Modeling & Management of Emergent Economy (M3E2-MLPEED 2021), Odessa, Ukraine, May 26-28, 2021, volume 3048 of CEU Workshop Proceedings, CEUR-WS.org, 2021, pp. i-xxxi. URL: https://ceur-ws.org/Vol-3048/ paper00.pdf.

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5. [5] S. Semerikov, Educational Technology Quarterly: in the beginning, Educational Technology Quarterly 2021 (2021) 1-50. doi:10.55056/etq.13.

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