NONLINEAR WAVE PROCESSES IN ACOUSTICS

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The investigation of nonlinear phenomena in acoustics has a rich history stretching back to the mechanical physical sciences in the nineteenth century. The study of nonlinear phenomena, such as explosions and jet engines, prompted the sharp growth of interest in nonlinear acoustic phenomena. In this book, the authors consider models of different "acoustic" media as well as equations and behavior of finite-amplitude waves. The authors also consider the effects of nonlinearity, dissipation, dispersion, and for two- and three-dimensional problems, reflection and diffraction on the evolution and interaction of acoustic beams. This book will be of interest not only to specialists in acoustics, but also to a wide audience of mathematicians, physicists, and engineers working on nonlinear waves in various physical systems.

Linear and Nonlinear Optimization using Spreadsheets (1版)

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【簡介】 The use of spreadsheets to obtain solutions to a diverse array of examples offers a reader-friendly way of addressing a topic (optimization) that can sometimes be viewed as intimidating. Many people are readily familiar with spreadsheets and how they work, yet are apt to be unaware of the incredible power of Excel for solving some rather complex optimization problems. A major goal of the book is to sell readers on why it is so important to understand optimization, and a large collection of examples for a wide range of business decision making areas (e.g., production planning and scheduling, workforce planning and scheduling, location and supply chain distribution, location of emergency services, assembly line balancing, vehicle routing, project scheduling, revenue management, advertising, product design, payout schedules, productivity measurement, investment portfolio management, sports league scheduling, ranking models, etc.) affords a practical mechanism for achieving that goal. Another important contribution of the book is that it provides coverage of the mechanics of some common yet sophisticated statistical methods (regression, logistic regression, discriminant analysis, factor analysis, and cluster analysis), which are often opaque to many users of such methods. 【目錄】 Introduction Optimization Examples in Prescriptive Analytics: Production Planning Workforce Planning Continuous Facility Location Discrete Facility Location Routing Problems Facility Layout Project Scheduling Marketing Finance Sports Optimization Examples for Multivariate Statistical Methods Used in Predictive and Descriptive Analytics: Regression Logistic Regression Linear Discriminant Analysis Factor Analysis Cluster Analysis