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The Art of Modeling Dynamic Systems: Forecasting for Chaos, Randomness and Determinism (Dover Books on Computer Science) [Paperback]

Foster Morrison
4.2 out of 5 stars  See all reviews (11 customer reviews)

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Book Description

January 24, 2008 0486462951 978-0486462950 2nd Ed 2008 Dover Ed
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.

Frequently Bought Together

The Art of Modeling Dynamic Systems: Forecasting for Chaos, Randomness and Determinism (Dover Books on Computer Science) + An Introduction to Mathematical Modeling (Dover Books on Computer Science) + Stochastic Modeling: Analysis and Simulation (Dover Books on Mathematics)
Price for all three: $45.20

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Editorial Reviews

From the Publisher

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. --This text refers to an out of print or unavailable edition of this title.

Product Details

  • Series: Dover Books on Computer Science
  • Paperback: 414 pages
  • Publisher: Dover Publications; 2nd Ed 2008 Dover Ed edition (January 24, 2008)
  • Language: English
  • ISBN-10: 0486462951
  • ISBN-13: 978-0486462950
  • Product Dimensions: 8.5 x 6 x 0.8 inches
  • Shipping Weight: 1 pounds (View shipping rates and policies)
  • Average Customer Review: 4.2 out of 5 stars  See all reviews (11 customer reviews)
  • Amazon Best Sellers Rank: #87,961 in Books (See Top 100 in Books)

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Customer Reviews

4.2 out of 5 stars
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Most Helpful Customer Reviews
19 of 19 people found the following review helpful
4.0 out of 5 stars Mathematical Depth and Descriptive Simplicity May 20, 2005
By X42
I find myself agreeing with all the comments made so far.

It's not too common to find a book that is able to describe in simple terms, such a large and diverse range of mathematical tools.

The author uses a framework - to tie together tools used in describing and handling deterministic, semi deterministic, and stochastic systems. For an example of Deterministic, try ODE's (ordinary differential equations), for semi deterministic - try Periodic but noisy wave-forms (some stock prices), and finally Stochastic - Random looking waveforms that have underlying patterns that can be described using either using Chaotic indicators (Hurst, Liapunov ) or probability type descriptors.

This book is the kind of thing you needed to help steer you through those dry mathematical books that are divorced from reality - A sort of classification system for deciphering what kind of gunpowder was used in those display's of intellectual fireworks from the tops of ivory towers. Kinda "So thats what all that maths means, but in plain english".

A depth of understanding, for practical application, without intellectual egotism and opaqueness. (But then maybe I'm just a bit thick ... :)

I'd tend to call this book as an equivalent to the Rosetta Stone for the maths of dynamical systems.

You may not use it directly - but you will benefit and grow in understanding from its' plain and simple sign posts along your journey.

It has its place on my book shelf.
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22 of 24 people found the following review helpful
5.0 out of 5 stars Single best reference for "modern" applied modeling September 29, 1998
By A Customer
This is a fantastic book and I'm sorry it's hard to get now. I found it by accident in a used book store in Madison, WI, in 1995 and found I learned a lot from it, even though by that time I had already taken multiple classes in Differential Equations, Linear Algebra, Statistics, etc. Dr. Morrison really sets out in lucid detail many of the important developments in applied modeling theory--dynamical systems, stochastic systems, the fudamentals that lie behind them--from a very useful perspective, and one that is often missing from the orthodox academic treatments. What he chooses not to cover in detail he references thoroughly. I wish that I had had this book when I was learning many of the topics. Anyone who is seriously considering learning dynamic modeling should read this book and I have little doubt that fairly experienced modelers will find something between the covers.
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11 of 11 people found the following review helpful
5.0 out of 5 stars A masterpiece January 24, 2002
By jerry f
This is the kind of book that should be available in every area of science and mathematics. A book that is not a research book, but yet is not a broad popularization. This book can benefit both persons who are just beginning a study of dynamic modeling and I dare say things will be learned by even those that are researchers in the area. Good work Foster Morrison whoever you are.
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7 of 8 people found the following review helpful
2.0 out of 5 stars bizarre February 19, 2013
Format:Hardcover|Verified Purchase
I'm surprised to see rave reviews of this strange book.
It did not help me to get an overview of the ideas
and practical issues in modeling dynamic systems.

I applaud the author for attempting to distill what he
has learned in his career (and the book does feel like
a career retrospective), but the book feels like a
loosely-organized collection of miscellaneous observations.

For example, the first part of the book covers mathematical
foundations. Instead of clearly covering basic concepts and
intuitions in each of the relevant areas, the author simply
makes a bunch of personal insights. I found them mostly useless
for areas I don't know, and strange or misleading for
areas I do know.

As another example of the book's strangeness, in the first
chapter he spends some time discussing constructive mathematics,
which does not seem to be something he understands well, or
that is relevant to the rest of the book.

Edit: I picked up the book tonight to see if I have
exaggerated. Perhaps "a loosely-organized collection of
miscellaneous observations" is a bit strong. But looking,
for example, at the "classical analysis" chapter, I can't
see that it achieves the author's goal: to "tell the
general reader what this material attempts to do and give
a new perspective on it to those already possessing this
training". And as an example of the kinds of strange
comments found throughout the book, section 17.2, on
Markov processes, starts with "The Markov chain assumes
that an adequate description of a system is given by a
finite number of state values."

Still, the author deserves credit for aiming to fill
the gap between technical books and popularizations.
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7 of 8 people found the following review helpful
4.0 out of 5 stars A broad overview November 21, 2001
By A Customer
Very general overview for the subject of dynamic systems modeling, providing ample historical perspectives. Not suitable for folks looking for deep technical matters.
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2 of 2 people found the following review helpful
5.0 out of 5 stars A resource for prospective modelers June 11, 2012
Format:Paperback|Verified Purchase
This book is one of a few that fills such a need for those seeking to develop their own models of dynamic systems. It asks you to casually re-examine the natural world and challenges you to come up with a way to view dynamic and interdependent systems mathematically. It explains the role of research and how to develop your own methods and approaches by keeping perspective with other disciplines. Truly a help in identifying relationships and attempting to express them mathematically.
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