Computational Methods in Engineering, AI, and Analysis
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Home > Mathematics and Science books > Mathematics > Calculus and mathematical analysis > Numerical analysis > Computational Methods in Engineering, AI, and Analysis: Mathematical Modeling, Machine Learning, Optimization, and Statistical Analysis(De Gruyter Proceedings in Mathematics)
Computational Methods in Engineering, AI, and Analysis: Mathematical Modeling, Machine Learning, Optimization, and Statistical Analysis(De Gruyter Proceedings in Mathematics)

Computational Methods in Engineering, AI, and Analysis: Mathematical Modeling, Machine Learning, Optimization, and Statistical Analysis(De Gruyter Proceedings in Mathematics)


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About the Book

Computational Methods in Engineering, AI, and Analysis offers a comprehensive concept  of modern computational mathematics, bringing together theoretical foundations, advanced numerical methods, and emerging data-driven approaches. The volume is structured across three key themes: mathematical modeling and computational techniques, engineering and physical system applications, and artificial intelligence with machine learning. It presents a collection of the methodologies such as wavelet-based methods, fractional calculus, finite element analysis, and hybrid AI models, with applications to the real-world problems in fluid dynamics, finance, healthcare, and environmental systems. With the contributions from the researchers across interdisciplinary fields, the book highlights the growing interaction between mathematics and the computational domain with the involvement of the advanced computational techniques to address the complex scientific challenges. 



About the Author :

Dr. Geeta Arora received her Ph.D. from IIT Roorkee, India, in 2011 and is currently a Professor in the Department of Mathematics at Lovely Professional University, Punjab. She has published around 65 Scopus-indexed research papers and authored 15 book chapters. Additionally, she has written a book on Vedic Mathematics and another on Essential Statistics, and she has edited a book on numerical methods for Taylor & Francis and IGI Global. Her research focuses on numerical methods and statistics. She has supervised 9 Ph.D. scholars and is currently guiding six. Her ongoing and published international books are in Taylor & Francis, IGI Publication and Elsevier.


Professor H. M. Srivastava is a distinguished researcher with a prolific output in mathematics. He has authored and co-authored numerous research papers published in leading international journals. His work has garnered recognition, as evidenced by his inclusion as a Highly Cited Researcher multiple times and his ranking among Canada's top researchers in mathematics. Moreover, he has edited several volumes and served on the editorial boards of multiple scientific journals, demonstrating his commitment to advancing mathematical research and education. His ongoing research interests include real and complex analysis, integral equations, and the study of higher transcendental functions, further solidifying his position as a leader in the mathematical community.

Dr Carlo Cattani is a Habil. Full Professor of Mathematical Physics and Applied Mathematics at Tuscia University (VT), Italy, since 2015. Previously, he was a professor at the University of Rome “La Sapienza” (1980-2004) and the University of Salerno (2004-2015). His research focuses on numerical methods, mathematical modeling, time series analysis, and artificial intelligence, with over 300 publications and several co-authored books. Cattani is the Editor in Chief of "Fractal and Fractional" and "Information Sciences Letters," and he has received honorary professorships from various universities, including Azerbaijan University (2019) and Harran University (2022). He was also an Adjunct Professor at Ton Duc Thang University in Vietnam (2018-2021).

Dr. Mamta Kapoor is currently working as an Associate Professor-Research in the Marwadi University Research Center, Department of Mathematics, Faculty of Engineering & Technology, Marwadi University, Rajkot, India. Her research focuses on the numerical approximation of linear and non-linear partial differential equations, as well as the semi-analytical solutions of fractional partial differential equations. Her work has been featured in leading journals and she serves as a Guest Editor for several high-profile journals and regularly review for various international journals.
Moreover, she is a detail-oriented and results-driven data science enthusiast with extensive training in data analytics, machine learning, and data visualization. 

S.A. Edalatpanah is an Associate Professor at Ayandegan Institute of Higher Education, Iran, recognized as one of the world's top 2% scientists by Elsevier and Stanford University from 2021 to 2023. He serves as the Vice President for Research & Development at the institute. His research interests encompass various aspects of computational intelligence, including fuzzy and neutrosophic theories. Edalatpanah has an extensive teaching portfolio, covering subjects from decision-making and numerical analysis to fuzzy systems and machine learning. His recent research projects and publications reflect his commitment to advancing knowledge in mathematical programming, operational research, and decision support systems.


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Product Details
  • ISBN-13: 9783119142816
  • Publisher: De Gruyter
  • Publisher Imprint: de Gruyter
  • Height: 240 mm
  • No of Pages: 540
  • Series Title: De Gruyter Proceedings in Mathematics
  • Width: 170 mm
  • ISBN-10: 3119142816
  • Publisher Date: 31 Aug 2026
  • Binding: Hardback
  • Language: English
  • Returnable: Y
  • Sub Title: Mathematical Modeling, Machine Learning, Optimization, and Statistical Analysis


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Computational Methods in Engineering, AI, and Analysis: Mathematical Modeling, Machine Learning, Optimization, and Statistical Analysis(De Gruyter Proceedings in Mathematics)
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