Novel Mathematics Inspired by Industrial Challenges -

Novel Mathematics Inspired by Industrial Challenges

Buch | Softcover
XXI, 337 Seiten
2023 | 1st ed. 2022
Springer International Publishing (Verlag)
978-3-030-96175-6 (ISBN)
96,29 inkl. MwSt
This contributed volume convenes a rich selection of works with a focus on innovative mathematical methods with applications in real-world, industrial problems. Studies included in this book are all motivated by a relevant industrial challenge, and demonstrate that mathematics for industry can be extremely rewarding, leading to new mathematical methods and sometimes even to entirely new fields within mathematics.
The book is organized into two parts: Computational Sciences and Engineering, and Data Analysis and Finance. In every chapter, readers will find a brief description of why such work fits into this volume; an explanation on which industrial challenges have been instrumental for their inspiration; and which methods have been developed as a result. All these contribute to a greater unity of the text, benefiting not only practitioners and professionals seeking information on novel techniques but also graduate students in applied mathematics, engineering, and related fields.

lt;p>Michael Günther got his PhD in Computer Science from TU München, Germany (1995) and the habilitation in Mathematics from the Universität Karlsruhe, Germany (2002). In 2003, he became a Full Professor in Applied Mathematics at Bergische Universität Wuppertal. His research is on time-domain simulation of coupled dynamical systems, ranging from ODEs, SDEs, DAEs to P(D)AEs, with applications in computational engineering, physics and finance, covering the whole spectrum from modeling to analysis and computational mathematics. He is Editor-In-Chief of both the journal and ECMI-subseries on "Mathematics in Industry" with Springer.

Wil Schilders holds a PhD (1998) from the Trinity College Dublin, Ireland. He studied mathematics, physics and astronomy at the Radboud University in Nijmegen, Netherlands, from 1974 to 1978. He developed numerical methods for semiconductor device simulation and electronic circuit simulation, and worked also on many other challenges in the electronics industry. In 1999, he became a part-time professor at Eindhoven University of Technology. In 2010, he extended his position at TU Eindhoven. His research concentrates on combinations of physics-based and data-based methods for solving advanced problems from industry, bridging the gap with academic mathematics.

Part I:  Computational Science and Engineering.- Multirate Schemes - An Answer of Numerical Analysis to a Demand from Applications.- Electronic Circuit Simulation and the Development of New Krylov-Subspace Methods.- Modular time integration of coupled problems in system dynamics.- Differential-Algebraic Equations and Beyond: From Smooth to Nonsmooth Constrained Dynamical Systems.- Fast Numerical Methods to Compute Periodic Solutions of Electromagnetic Models.- Challenges in the Simulation of Radio Frequency Circuits.- An integrated data-driven computational pipeline with model order reduction for industrial and applied mathematics.- From rotating fluid masses and Ziegler's paradox to Pontryagin- and Krein spaces and bifurcation theory.- Part II: Data Analysis and finance.- Topological Data Analysis.- Prediction Models with Functional Data for Variables related with Energy Production.- Quantization Methods for Stochastic Differential Equations.

Erscheinungsdatum
Reihe/Serie Mathematics in Industry
The European Consortium for Mathematics in Industry
Zusatzinfo XXI, 337 p. 95 illus., 63 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 551 g
Themenwelt Mathematik / Informatik Mathematik Angewandte Mathematik
Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
Schlagworte application driven research • Applied mathematics • Complex Data • computational science and engineering • data analysis and finance • Discrete Mathematics • functional data analysis • Industrial Mathematics • Industrial Problems • machine learning • Numerical analysis • Persistent Homology • Prediction models • Quantization Methods • Stochastic differential equations • TDA • topological data analysis
ISBN-10 3-030-96175-3 / 3030961753
ISBN-13 978-3-030-96175-6 / 9783030961756
Zustand Neuware
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