Applied and Computational Mathematics – Applications in Finance and Data Science
AACM-2025, Mesra, India, February 13–15
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Beschreibung
This book discusses the topics presented at the 2nd Annual QEDS Conference on “Advances in Applied and Computational Mathematics: Theory, Methods, and Applications in Finance and Data Science (AACM 2025)”, organized by the Centre for Quantitative Economics and Data Science, Birla Institute of Technology Mesra, Ranchi, Jharkhand, India, from February 13–15, 2025. This book focuses on the convergence of applied and computational mathematics with finance, data science, and data-driven public policy. It highlights recent research contributions in areas such as mathematical optimization, simulation techniques, statistical modelling, and algorithmic developments, emphasizing their growing relevance in engineering, finance, and data science.
Chapters in the book reflect both theoretical advancements and practical methodologies that address contemporary challenges in an increasingly data-centric world. This book is carefully curated for a broad readership, including researchers, industry professionals, and policy experts from diverse academic and professional backgrounds. It offers valuable insights for those seeking to deepen their understanding and remain current in rapidly evolving technological and analytical domains. For the academic community, this book serves as an essential resource for students, educators, and researchers in mathematics, statistics, data science, finance, and related fields.
This book discusses the topics presented at the 2nd Annual QEDS Conference on “Advances in Applied and Computational Mathematics: Theory, Methods, and Applications in Finance and Data Science (AACM 2025)”, organized by the Centre for Quantitative Economics and Data Science, Birla Institute of Technology Mesra, Ranchi, Jharkhand, India, from February 13–15, 2025. This book focuses on the convergence of applied and computational mathematics with finance, data science, and data-driven public policy. It highlights recent research contributions in areas such as mathematical optimization, simulation techniques, statistical modelling, and algorithmic developments, emphasizing their growing relevance in engineering, finance, and data science.
Chapters in the book reflect both theoretical advancements and practical methodologies that address contemporary challenges in an increasingly data-centric world. This book is carefully curated for a broad readership, including researchers, industry professionals, and policy experts from diverse academic and professional backgrounds. It offers valuable insights for those seeking to deepen their understanding and remain current in rapidly evolving technological and analytical domains. For the academic community, this book serves as an essential resource for students, educators, and researchers in mathematics, statistics, data science, finance, and related fields.
Emphasizes mathematical foundations on graph theory, combinatorics, coding theory, numerical analysis, and optimization Focuses on the development of statistical methodologies for complex data scenarios Presents a comprehensive treatment of stochastic and queueing models
Autor*in
Mrinal Jana
Themen in »Applied and Computational Mathematics – Applications in Finance and Data Science«
mathematical modeling computational mathematics numerical analysis statistical theory data science graph theory Hull dimesion Levenberg-Marquardt neural network approach phasor measurement Bruijn graphs Weibull populations deterministic datasets discrete-time vacation queue heuristic bilevel approach portfolio problems