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Earthquake Statistical Analysis through Multi-state Modeling


Earthquake Statistical Analysis through Multi-state Modeling


1. Aufl.

von: Irene Votsi, Nikolaos Limnios, Eleftheria Papadimitriou, George Tsaklidis

139,99 €

Verlag: Wiley
Format: PDF
Veröffentl.: 03.01.2019
ISBN/EAN: 9781119579069
Sprache: englisch
Anzahl Seiten: 192

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Beschreibungen

<p>Earthquake occurrence modeling is a rapidly developing research area. This book deals with its critical issues, ranging from theoretical advances to practical applications.<br /> <br /> The introductory chapter outlines state-of-the-art earthquake modeling approaches based on stochastic models. Chapter 2 presents seismogenesis in association with the evolving stress field. Chapters 3 to 5 present earthquake occurrence modeling by means of hidden (semi-)Markov models and discuss associated characteristic measures and relative estimation aspects. Further comparisons, the most important results and our concluding remarks are provided in Chapters 6 and 7.</p>
<p>List of Abbreviations ix</p> <p>List of Symbols xi</p> <p>Preface xv</p> <p>Introduction xix</p> <p><b>Chapter 1. Fundamentals on Stress Changes 1</b></p> <p>1.1. Introduction 1</p> <p>1.2. Stress interaction 4</p> <p>1.3. Stress changes calculation 12</p> <p>1.4. Modeling of Coulomb stress changes for different faulting types 15</p> <p>1.4.1.ΔCS for strike-slip faulting 15</p> <p>1.4.2.ΔCS for dip-slip faulting 16</p> <p>1.5. Seismicity triggered by stress transfer 21</p> <p>1.5.1. Triggering of strong earthquakes 21</p> <p>1.5.2. Aftershock triggering 23</p> <p>1.5.3. Triggering of mining seismicity 28</p> <p>1.6. Discussion on stress interaction 31</p> <p><b>Chapter 2. Hidden Markov Models 35</b></p> <p>2.1. Introduction 35</p> <p>2.2. Hidden Markov framework 37</p> <p>2.3. Seismotectonic regime and seismicity data 42</p> <p>2.4. Application to earthquake occurrences 44</p> <p>2.4.1. Two hidden states and three observation types 45</p> <p>2.4.2. Three hidden states and three observation types 48</p> <p>2.4.3. Model selection and simulation 50</p> <p>2.4.4. Steps number for the first earthquake occurrence 53</p> <p>2.5. Conclusion 54</p> <p><b>Chapter 3. Hidden Markov Renewal Models 57</b></p> <p>3.1. Introduction 57</p> <p>3.2. Semi-Markov framework 58</p> <p>3.3. Hidden Markov renewal framework 65</p> <p>3.4. Modeling earthquakes in Greece 66</p> <p>3.4.1. Hitting times and earthquake occurrence numbers 69</p> <p>3.5. Conclusion 73</p> <p><b>Chapter 4. Hitting Time Intensity 75</b></p> <p>4.1. Introduction 75</p> <p>4.2. DTIHT for semi-Markov chains 76</p> <p>4.2.1. Statistical estimation of the DTIHT 78</p> <p>4.3. DTIHT for hidden Markov renewal chains 83</p> <p>4.3.1. Statistical estimation of the DTIHT 85</p> <p>4.4. Conclusion 87</p> <p><b>Chapter 5. Models Comparison 89</b></p> <p>5.1. Introduction 89</p> <p>5.2. Markov framework 90</p> <p>5.2.1. HMM case 92</p> <p>5.2.2. HMRM case 92</p> <p>5.3. Markov renewal framework 93</p> <p>5.3.1. HMM case 95</p> <p>5.3.2. HMRM case 96</p> <p>5.4. Conclusion 97</p> <p>Discussion & Concluding Remarks 99</p> <p>Appendices 105</p> <p>Appendix 1 107</p> <p>Appendix 2 113</p> <p>Appendix 3 117</p> <p>References 119</p> <p>Index 137</p>
<p><b>Irene Votsi</b> is Assistant Professor of Statistics at the Manceau Laboratory of Mathematics, Le Mans University, France.</p> <p><b>Nikolaos Limnios</b> is Professor of Applied Mathematics at the University of Technology of Compiègne, Sorbonne University, France.</p> <p><b>Eleftheria Papadimitriou</b> is Professor of Seismology at the Aristotle University of Thessaloniki, Greece.</p> <p><b>George Tsaklidis</b> is Professor of Probability and Statistics at the Aristotle University of Thessaloniki, Greece.</p>

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