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  • © 2013

Linear Models in the Mathematics of Uncertainty

  • This books describes and discusses linear models in the mathematics of uncertainty including analytic hierarchy method, data fusion, and evidence theory
  • This book also provides some applications of these methods to a range of different practical situations
  • Written by leading experts in the field

Part of the book series: Studies in Computational Intelligence (SCI)

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Table of contents (15 chapters)

  1. Back Matter

    Pages 239-263

About this book

The purpose of this book is to present new mathematical techniques for modeling global issues. These mathematical techniques are used to determine linear equations between a dependent variable and one or more independent variables in cases where standard techniques such as linear regression are not suitable.

In this book, we examine cases where the number of data points is
small (effects of nuclear warfare), where the experiment is not repeatable (the breakup of the former Soviet Union), and where the data is derived from expert opinion (how conservative is a political party). In all these cases the data  is difficult to measure and an assumption of randomness and/or statistical validity is questionable. 

We apply our methods to real world issues in international relations such as  nuclear deterrence, smart power, and cooperative threat reduction. We next apply our methods to issues in comparative politics such as successful democratization, quality of life, economic freedom, political stability, and failed states. Finally, issues involving deaf and hard of hearing children are explored.
 

Reviews

From the reviews:

“The research monograph is devoted to a plethora of decision-making problems whose structure involves combinations (aggregations) of causal factors. … the material is carefully structured and makes the book self-contained and easy to read to novices and those not fully familiar with the background ideas. … This coherently organized reading … will offer the reader a breadth and rigor of the technology of fuzzy sets and comes as a testimony to the need and usefulness of the technology of coping with uncertainty to real-world problems.” (Witold Pedrycz, zbMATH, Vol. 1268, 2013)

Authors and Affiliations

  • , Department of Mathematics, Creighton University, Omaha, USA

    John N. Mordeson, Alex Pham, Michael A. Redmond

  • , Department of Computer Science, Creighton University, Omaha, USA

    Mark J. Wierman

  • , Department of Political Science, Creighton University, Omaha, USA

    Terry D. Clark

Bibliographic Information

  • Book Title: Linear Models in the Mathematics of Uncertainty

  • Authors: John N. Mordeson, Mark J. Wierman, Terry D. Clark, Alex Pham, Michael A. Redmond

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-642-35224-9

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2013

  • Hardcover ISBN: 978-3-642-35223-2Published: 02 February 2013

  • Softcover ISBN: 978-3-642-43880-6Published: 07 March 2015

  • eBook ISBN: 978-3-642-35224-9Published: 01 February 2013

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XXVIII, 265

  • Number of Illustrations: 7 b/w illustrations, 8 illustrations in colour

  • Topics: Computational Intelligence

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access