Numerical Methods and Modelling for Engineering

Khoury, Richard (Author)/ Harder, Douglas Wilhelm (Author)

ISBN 10: 3319211757 / ISBN 13: 9783319211756

Edité par Springer, 2016

A propos de cet article

9.25x6.25x1.00 inches. In Stock.

N° de réf. du vendeur x-3319211757

Détails bibliographiques

• Titre: Numerical Methods and Modelling for Engineering
• Éditeur: Springer
• Date de parution: 2016
• Langue: anglais
• ISBN à 10 chiffres: 3319211757
• ISBN à 13 chiffres: 9783319211756
• Reliure: Hardcover
• État de l'article: Brand New

A propos de ce titre

Synopsis

This textbook provides a step-by-step approach to numerical methods in engineering modelling. The authors provide a consistent treatment of the topic, from the ground up, to reinforce for students that numerical methods are a set of mathematical modelling tools which allow engineers to represent real-world systems and compute features of these systems with a predictable error rate. Each method presented addresses a specific type of problem, namely root-finding, optimization, integral, derivative, initial value problem, or boundary value problem, and each one encompasses a set of algorithms to solve the problem given some information and to a known error bound. The authors demonstrate that after developing a proper model and understanding of the engineering situation they are working on, engineers can break down a model into a set of specific mathematical problems, and then implement the appropriate numerical methods to solve these problems.

À propos de l?auteur

Richard Khoury received his Bachelor's Degree and his Master's Degree in Electrical and Computer Engineering from Laval University (Québec City, QC) in 2002 and 2004 respectively, and his Doctorate in Electrical and Computer Engineering from the University of Waterloo (Waterloo, ON) in 2007. Since August 2008, he is a faculty member in the Department of Software Engineering at Lakehead University. Dr. Khoury's primary area of research is natural language processing, but his research interests also include data mining, knowledge management, machine learning, and artificial intelligence.