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Книга "Bayesian Methods for Structural Dynamics & Civil Engineering" помогает студентам, исследователям и практикующим инженерам в применении статистических методов для решения инженерных задач, а также проработке различных задач в области динамической и статической систем. Автором книги является Ka-Veng Yuen, ведущий эксперт в использовании байесовских методов в гражданских и механических конструкциях или прикладной теории вероятности и статистики.
Такие темы, как идентификация, динамические и статические системы, обновление моделей, механические и космические системы, моделирование повреждений по искусственной нейронной сети для мониторинга состояния конструкции и прогнозирования качества воздуха, являются ключевыми в книге.
Доступны ресурсы в формате MATLAB, код и лекции для преподавателей, другие подсказки для исследователей и студентов, что делает книгу лучшим выбором для инженеров и желающих углубиться в статистический анализ материалов.
Bayesian Methods offers simple explanations of complex theoretical concepts which may be used by various probability theory researchers. By navigating its pages, this text expert readers if you're aiming to gain a solid grasp on the material. The written topics are overall well – conceived, balanced , and logically connected for maximum understanding by both casual mathematical researchers and theoretical physicists.
Электронная Книга «Bayesian Methods for Structural Dynamics and Civil Engineering» написана автором Ka-Veng Yuen в году.
Минимальный возраст читателя: 0
Язык: Английский
ISBN: 9780470824559
Описание книги от Ka-Veng Yuen
Bayesian methods are a powerful tool in many areas of science and engineering, especially statistical physics, medical sciences, electrical engineering, and information sciences. They are also ideal for civil engineering applications, given the numerous types of modeling and parametric uncertainty in civil engineering problems. For example, earthquake ground motion cannot be predetermined at the structural design stage. Complete wind pressure profiles are difficult to measure under operating conditions. Material properties can be difficult to determine to a very precise level – especially concrete, rock, and soil. For air quality prediction, it is difficult to measure the hourly/daily pollutants generated by cars and factories within the area of concern. It is also difficult to obtain the updated air quality information of the surrounding cities. Furthermore, the meteorological conditions of the day for prediction are also uncertain. These are just some of the civil engineering examples to which Bayesian probabilistic methods are applicable. Familiarizes readers with the latest developments in the field Includes identification problems for both dynamic and static systems Addresses challenging civil engineering problems such as modal/model updating Presents methods applicable to mechanical and aerospace engineering Gives engineers and engineering students a concrete sense of implementation Covers real-world case studies in civil engineering and beyond, such as: structural health monitoring seismic attenuation finite-element model updating hydraulic jump artificial neural network for damage detection air quality prediction Includes other insightful daily-life examples Companion website with MATLAB code downloads for independent practice Written by a leading expert in the use of Bayesian methods for civil engineering problems This book is ideal for researchers and graduate students in civil and mechanical engineering or applied probability and statistics. Practicing engineers interested in the application of statistical methods to solve engineering problems will also find this to be a valuable text. MATLAB code and lecture materials for instructors available at http://www.wiley.com/go/yuen
