Overview

This text presents both a comprehensive framework for characterizing all forms of systems problems, and a set of specific methodologies for some key problems. These methodologies are based on a combination of classical and fuzzy set theories, probability and possibility theories, graph and hypergraph theories, and information theory, among others. The hardcopy text contains a revised, updated and condensed version of the first edition, accompanied by a CD containing supplementary material including additional chapters on related topics, explanatory material drawn from many years of class presentations and lectures, exercises, and fully worked out examples showing both the framework and methodology in operation on actual real-world problems. Fully operational software is made available on an associated website. The material is suitable for upper-level undergraduates and first-year graduate students with a modest background in discrete mathematics, probability and statistics.

Full Product Details

Author:   George J. Klir ,  Doug Elias
Publisher:   Springer Science+Business Media
Imprint:   Kluwer Academic/Plenum Publishers
Edition:   2nd ed. 2003
Volume:   21
Dimensions:   Width: 15.50cm , Height: 2.70cm , Length: 23.50cm
Weight:   0.717kg
ISBN:  

9780306473579

ISBN 10:   0306473577
Pages:   349
Publication Date:   31 January 2003
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   Out of stock  
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

Table of Contents

1 Introduction.- 1.1 Systems Science.- 1.2 Systems Problem Solving.- 1.3 Hierarchy of Epistemological Levels of Systems.- 1.4 The Role of Mathematics.- 1.5 The Role of Computer Technology.- 1.6 Architecture of Systems Problem Solving.- 2 Source and Data Systems.- 2.1 Objects and Object Systems.- 2.2 Variables and Supports.- 2.3 Methodological Distinctions.- 2.4 Discrete versus Continuous.- 2.5 Image Systems and Source Systems.- 2.6 Data Systems.- 3 Generative Systems.- 3.1 Empirical Investigation.- 3.2 Behavior Systems.- 3.3 Methodological Distinctions.- 3.4 From Data Systems to Behavior Systems.- 3.5 Measures of Uncertainty.- 3.6 Search for Admissible Behavior Systems.- 3.7 State-Transition Systems.- 3.8 Generative Systems.- 3.9 Simplification of Generative Systems.- 3.10 Systems Inquiry and Systems Design.- 4 Structure Systems.- 4.1 Wholes and Parts.- 4.2 Systems, Subsystems, Supersystems.- 4.3 Structure Source Systems and Structure Data Systems.- 4.4 Structure Behavior Systems.- 4.5 Problems of Systems Design.- 4.6 Identification Problem.- 4.7 Reconstruction Problem.- 4.8 Reconstructability Analysis.- 4.9 Simulation Experiments.- 4.10 Inductive Reasoning.- 4.11 Inconsistent Structure Systems.- 5 Metasystems.- 5.1 Change versus Invariance.- 5.2 Primary and Secondary Systems Traits.- 5.3 Metasystems.- 5.4 Metasystems versus Structure Systems.- 5.5 Multilevel Metasystems.- 5.6 Identification of Change.- 6 GSPS: Architecture, Use, Evolution.- 6.1 Epistemological Hierarchy of Systems : Formal Definition.- 6.2 Methodological Distinctions: A Summary.- 6.3 Problem Requirements.- 6.4 Systems Problems.- 6.5 GSPS Conceptual Framework: Formal Definition.- 6.6 Overview of GSPS Architecture.- 6.7 GSPS Use: Some Case Studies.- 6.8 GSPS Evolution.- Author Index.

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