This text illustrates the roles of statistical methods, coordinate transformations, and mathematical analysis in mapping complex, unpredictable dynamical systems. It describes the benefits and limitations of the available modeling tools, showing engineers and scientists how any system can be rendered simpler and more predictable.
Written by a well-known authority in the field, this volume employs practical examples and analogies to make models more meaningful. The more universal methods appear in considerable detail, and advanced dynamic principles feature easy-to-understand examples. The text draws careful distinctions between mathematical abstractions and observable realities. Additional topics include the role of pure mathematics, the limitations of numerical methods, forecasting in the presence of chaos and randomness, and dynamics without calculus. Specialized techniques and case histories are coordinated with a carefully selected and annotated bibliography. The original edition was a Library of Science Main Selection in May, 1991. This new Dover edition features corrections by the author and a new Preface.
In the coverage of dynamics, there is a definite gap between ``picture-book'' popularizations and the technical literature. This work fills that gap. Shows engineers and scientists how, by the application of statistical methods, coordinate transformations and mathematical analysis, any complex, unpredictable dynamical system can be mapped--transformed into a simpler, predictable system. The various modeling tools available, their benefits and their limitations are described. Examples and analogies are used in place of theorems and proofs, making this an immediately practical book. By showing how to make models more meaningful and useful, it will be particularly helpful in clearing up the impasse between economics and system dynamics. Features a number of carefully selected references to more mathematical treatments, examples of some of the more specialized techniques and case histories of some models.