Bibliographic Information

Limits of predictability

Yurii A. Kravtsov (ed.)

(Springer series in synergetics, v. 60)

Springer-Verlag, c1993

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  • : us

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Includes bibliographical references and index

Description and Table of Contents

Description

One of the driving forces behind much of modern science and technology is the desire to foresee and thereby control the future. In recent years, however, it has become clear that, even in a deterministic world, there is alimit to the accuracy with which we can predict the future. This book details, in a largely nontechnical style, the extent to which we can predict the future development of various physical, biological and socio-economic processes.

Table of Contents

1. Introduction.- References.- 2. Forecasting Weather and Climate.- 2.1 Weather and Climate.- 2.2 Dynamical Systems and Their Properties.- 2.3 Weather Predictability.- 2.4 Elements of Stationary Random Process Prediction Theory.- 2.5 Predictability of Climatic Processes.- 2.6 Ways to Improve Statistical Forecasting.- 2.7 Utilization of Forecasting Results.- 2.8 Conclusion.- References.- 3. How an Active Autowave Medium Can Be Used to Predict the Future.- 3.1 Prediction.- 3.2 Active Autowave Media.- 3.3 Autowave Propagation in Energy-Restoring Active Media.- 3.4 Dynamics of Autowave Interaction.- 3.5 The External Medium Model and Its Fourier Image.- 3.6 Non-isochronism of Cyclic Processes.- 3.7 Harmonious Modulation and Modulation of Harmonics.- 3.8 The Fourier Image Cleared by the Active Autowave Medium.- References.- 4. Synergetics, Predictability and Deterministic Chaos.- 4.1 Dynamical Chaos.- 4.2 Nonlinearity and Open Systems Behavior.- 4.3 Synergetics and Order Parameters.- 4.4 Strangeness of the Strange Attractors.- 4.5 Dynamical Chaos and Reality.- 4.6 Dynamical Chaos. Gates of Fairyland.- References.- 5. The Information-Theoretic Approach to Assessing Reliability of Forecasts.- 5.1 Assessing Forecasts.- 5.2 Forecasting as the Subject Matter of Information Theory.- 5.3 An Example.- 5.4 Optimization of Forecasting Methods.- 5.5 Properties Shared by Prediction Methods.- 5.6 The Connection Between Discounting and Non-stationarity.- 5.7 Conclusion.- References.- 6. Prediction of Time Series.- 6.1 The Problem.- 6.2 Genesis of Random Phenomena.- 6.3 Time Series Prediction Based on Dynamical Chaos Theory.- 6.4 Prediction of Point Processes.- 6.5 The Nature of Errors Hindering Prediction.- 6.6 Prediction of Strong Earthquakes.- References.- 7. Fundamental and Practical Limits of Predictability.- 7.1 Predictability.- 7.2 Real, Observed, and Model Processes.- 7.3 Degree of Predictability. The Predictability Horizon.- 7.4 Searching for Prediction Models.- 7.5 Limits to Predictability.- 7.6 Dynamical Analogs to Social and Economic Phenomena.- 7.7 Conclusion.- References.- 8. The Future is Foreseeable but not Predictable: The 'Oedipus Effect' in Social Forecasting.- 8.1 Historical Background.- 8.2 The 'Oedipus Effect' in Social Forecasting.- 8.3 The Problem of Foresight and Prediction in Globalistics.- 8.4 The Problem of Foreseeing and Predicting the Development of the Former Soviet Society.- References.- Appendix A: Looking Back on the August 1991 Coup.- Appendix B: Looking Ahead.- 9. The Self-Organization of American Society in Presidential and Senatorial Elections.- 9.1 Historical Background.- 9.2 The American Presidential Election: Formal Analysis.- 9.3 Midterm Senatorial Elections: Formal Analysis.- 9.4 Discussion.- References.- 10. Problems of Predictability in Ethnogenic Studies.- References.

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Details
  • NCID
    BA20628003
  • ISBN
    • 354056277X
    • 038756277X
  • LCCN
    93007284
  • Country Code
    gw
  • Title Language Code
    eng
  • Text Language Code
    eng
  • Place of Publication
    Berlin ; Tokyo
  • Pages/Volumes
    xii, 252 p.
  • Size
    25 cm
  • Classification
  • Subject Headings
  • Parent Bibliography ID
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