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170905s2017 ne o 001 0 eng d |
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|a 018409939
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|a 1002847962
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|a 9780128040935
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|a 0128040939
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|z 0128040718
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|z 9780128040713
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|a Risk modeling for hazards and disasters /
|c edited by Gero Michel.
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260 |
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|a Amsterdam :
|b Elsevier,
|c 2017.
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300 |
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|a 1 online resource
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336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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500 |
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|a Includes index.
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0 |
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|a Print version record.
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|6 880-01
|a Front Cover; RISK MODELING FOR HAZARDS AND DISASTERS; RISK MODELING FOR HAZARDS AND DISASTERS; Copyright; Contents; List of Contributors; INTRODUCTION; References; I -- CATASTROPHE MODELS, GENERAL CONCEPTS AND METHODS; 1 -- Quantifying Model Uncertainty and Risk; INTRODUCTION; BACKGROUND OF CATASTROPHE MODELING; DIFFERENT COMPONENTS OF CATASTROPHE MODELS; EARTHQUAKE HAZARD; Components of Earthquake Source Models; Fault Sources; Distributed Sources; Smoothing of Seismicity; Smoothing of Historical Seismicity; Maximum Magnitude; Earthquake Probability Model; Ground Motion.
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|a EPISTEMIC UNCERTAINTY IN SEISMIC HAZARD RESULTSBUILDING VULNERABILITY; Methodology; Loss Distribution; Analytical Approach of Development of Vulnerability Functions; BUILDING COMPONENTS; DAMAGE STATES; REPAIR COSTS; PEER-PBEE-Based Analytical Approach; Damage Measure and Repair Cost; SECONDARY HAZARD AND SUBPERILS; METHODOLOGY FOR LOSS CALCULATIONS; LOSS RESULTS AND THE UNCERTAINTY; OVERVIEW OF A TYPICAL HURRICANE CATASTROPHE MODEL; COMPONENT LEVEL UNCERTAINTIES; Sensitivity to Numbers of Years and Numbers of Samples; Sensitivity to Choices for LTR Models.
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505 |
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|a Sensitivity to Choices for MTR ModelsSensitivity to Choices for Track, Intensity, Size, Transitioning, and Filling Rate Models; Sensitivities to Overland Wind-Field Models; Sensitivities to Vulnerabilities; Other Wind Uncertainties; Surge Uncertainties; Flood Uncertainties; SUMMARY; References; Further Reading; 2 -- What Makes a Catastrophe Model Robust; INTRODUCTION; PROMISE OF THE STOCHASTIC CATALOG; SIMULATION OF EVENT INTENSITIES AT LOCATION; MODELING DAMAGE; FINANCIAL MODEL AND VALIDATING LOSSES; CLOSING THOUGHTS; Acknowledgments; References; APPENDIX A; Stochastic Catalog.
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|a Conditional Exceedance ProbabilityCONCLUDING REMARKS; Acknowledgments; References; 4 -- Empirical Fragility and Vulnerability Assessment: Not Just a Regression; INTRODUCTION; CHALLENGES WITH POSTEVENT LOSS AND DAMAGE DATABASES; Postevent Loss and Damage Data Sources; Incomplete Data; Measurement and Classification Errors; Intensity; Asset Characteristics; Damage Scale; Loss; Multiple Successive Hazard Events; STATISTICAL MODELS -- WHICH MODEL FITS THE DATA BEST?; Introduction; Parametric Statistical Models; Nonlinear Models; Linear Models; Generalized Linear Models.
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650 |
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|a Risk assessment
|x Mathematical models.
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650 |
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0 |
|a Natural disasters
|x Risk assessment.
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650 |
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0 |
|a Hazard mitigation.
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650 |
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6 |
|a �Evaluation du risque
|0 (CaQQLa)201-0139195
|x Mod�eles math�ematiques.
|0 (CaQQLa)201-0379082
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650 |
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6 |
|a Catastrophes naturelles
|0 (CaQQLa)201-0018874
|x �Evaluation du risque.
|0 (CaQQLa)201-0385652
|
650 |
|
6 |
|a Catastrophes
|x R�eduction.
|0 (CaQQLa)201-0427726
|
650 |
|
7 |
|a BUSINESS & ECONOMICS
|x Industries
|x General.
|2 bisacsh
|
650 |
|
7 |
|a Hazard mitigation
|2 fast
|0 (OCoLC)fst01737034
|
650 |
|
7 |
|a Natural disasters
|x Risk assessment
|2 fast
|0 (OCoLC)fst01982424
|
650 |
|
7 |
|a Risk assessment
|x Mathematical models
|2 fast
|0 (OCoLC)fst01098155
|
700 |
1 |
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|a Michel, Gero.
|
776 |
0 |
8 |
|i Print version:
|t Risk modeling for hazards and disasters.
|d Amsterdam : Elsevier, 2017
|z 0128040718
|z 9780128040713
|w (OCoLC)974441099
|
856 |
4 |
0 |
|u https://sciencedirect.uam.elogim.com/science/book/9780128040713
|z Texto completo
|
880 |
8 |
|
|6 505-01/(S
|a Local IntensityDamage Functions; Financial Calculations; Overall Model; 3 -- Towards a More Dynamical Paradigm for Natural Catastrophe Risk Modeling; INTRODUCTION; LOSS SIMULATION; Event Loss Table Definition; Loss Distribution Functions: CEP, OEP, and AEP; CLUSTERING; Scientific Background; Overdispersion in Counts; Building Clustering into ELT Calculations; DYNAMICAL MIXTURE MODELS; Concept; Estimation of the Mixing Parameters: β0,i and β1,i; Choice of Row Overdispersion: Scaling Properties; Models and Simulations; Results; Clustering; Aggregate Exceedance Probability.
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