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Erscheint vorauss. 13. März 2025
  • Gebundenes Buch

This book offers a comprehensive treatment of the core mathematical topics required for a modern engineering degree. The book begins with an introduction to the basics of mathematical reasoning and builds up the level of complexity as it progresses.

Produktbeschreibung
This book offers a comprehensive treatment of the core mathematical topics required for a modern engineering degree. The book begins with an introduction to the basics of mathematical reasoning and builds up the level of complexity as it progresses.
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Autorenporträt
Francesc Pozo Montero received his degree in Mathematics from the University of Barcelona in 2000 and completed his PhD in Applied Mathematics at the Universitat Politècnica de Catalunya (UPC) in 2005. Since 2000, he has been a member of the Department of Mathematics at UPC, where he currently holds the position of Full Professor. He also serves as the coordinator of the Control, Data, and Artificial Intelligence research group and is recognized as a Senior Member of IEEE. Francesc Pozo Montero's research interests include condition monitoring, control systems, data-driven modeling, system identification, and structural health monitoring, with a particular emphasis on applications related to wind turbines. He is an Editorial Board Member for several prestigious international journals, including Structural Control and Health Monitoring (Wiley), International Journal of Distributed Sensor Networks (Wiley), Mathematical Problems in Engineering (Wiley), Mathematics (MDPI), Sensors (MDPI), Algorithms (MDPI), Journal of Vibration and Control (Sage), Frontiers in Built Environment (Frontiers), Frontiers in Energy Research (Frontiers), and Energies (MDPI). Francesc Pozo Montero has made substantial contributions to his field, authoring over 70 high-impact journal articles, participating in 23 competitive R&D&I projects, and writing 34 book chapters and 12 books. He has successfully supervised six PhD candidates, filed one invention patent, and established a collaboration contract with an industry partner. His work has also been presented in more than 130 conference papers. Núria Parés Mariné holds a degree in Mathematics (1999) and a PhD in Applied Mathematics (2005) from the Universitat Politècnica de Catalunya (UPC), Barcelona, Spain. As a Full Professor at UPC, she focuses on developing and advancing numerical methods applied to engineering. Over the years, her research has concentrated on three primary areas: result certification, model reduction techniques, and machine learning. Through her innovative approach, she has successfully collaborated with internationally renowned researchers, contributing significantly to the academic and scientific community. Núria Parés Mariné has made substantial contributions to her field, authoring over 25 high-impact journal articles and participating in 19 competitive R&D&I projects. Her prolific output also includes writing three book chapters and ten books. She has guided and supervised three PhD candidates to successful completions, showcasing her dedication to mentoring the next generation of researchers. In addition, she has been involved in technology transfer establishing a collaboration contract with an industry partner, bridging the gap between academia and real-world applications. Her work has been widely recognized and presented in more than 65 conference papers, illustrating her commitment to disseminating knowledge and sharing advancements with the broader scientific community. Prof. Parés continues to be a leading figure in her research areas, driving innovation and excellence in applied mathematics. Her ongoing efforts in integrating machine learning with traditional numerical methods are paving the way for new, groundbreaking approaches in engineering and related disciplines. Yolanda Vidal Seguí holds a degree in Mathematics (1999) and a PhD in Applied Mathematics (2005) from the Universitat Politècnica de Catalunya (UPC), Barcelona, Spain. As an Associate Professor at UPC and an IEEE Senior Member, she is deeply involved in multidisciplinary research, with a particular focus on the application of her expertise to wind turbines. Her research areas encompass condition monitoring, structural health monitoring, fault diagnosis and prognosis, predictive maintenance, machine learning, deep learning, artificial intelligence, and mathematical modeling. Yolanda Vidal Seguí serves on the Editorial Board of several prestigious international journals, including Engineering Applications of AI (Elsevier), Wind Energy (Wiley), Wind Energy Science (Copernicus), Journal of Vibration and Control (SAGE), IET Renewable Power Generation (IET), Mathematics (MDPI), Sensors (MDPI), Energies (MDPI), Frontiers in Built Environment, and Frontiers in Energy Research. Her prolific contributions to the field are demonstrated by over 70 high-impact journal articles, 23 competitive R+D+I projects, 17 book chapters, and 10 books. She has supervised 7 PhD theses, with 4 currently ongoing. Additionally, she holds 1 invention patent and has secured a collaboration contract with an industry partner. Dr. Vidal has also presented 120 conference papers, further showcasing her dedication and impact in her areas of expertise.