Description |
1 online resource (239 pages) |
Contents |
Front Cover; Dedication; Summary; Table of Contents; CHAPTER 1: INTRODUCTION; CHAPTER 2: CASE STUDY; CHAPTER 3: STORM SURGE MODELING; CHAPTER 4: COMPUTATIONAL INTELLIGENCE; CHAPTER 5: NONLINEAR DYNAMICS AND CHAOS THEORY; CHAPTER 6: BUILDING PREDICTIVE CHAOTIC MODEL; CHAPTER 7: ENHANCEMENTS: RESOLVING ISSUES OF HIGH DIMENSIONALITY, PHASE ERRORS, INCOMPLETENESS AND FALSE NEIGHBORS; CHAPTER 8: COMPUTATIONAL INTELLIGENCE IN IDENTIFYING OPTIMAL PREDICTIVE CHAOTIC MODEL; CHAPTER 9: REAL-TIME DATA ASSIMILATION USING NARX NEURAL NETWORK; CHAPTER 10: ENSEMBLE MODEL PREDICTION |
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Chapter 11: conclusions and recommendationsreferences; about the author; scientific publications; samenvatting |
Summary |
Accurate predictions of storm surge are of importance in many coastal areas in the world to avoid and mitigate its destructive impacts. For this purpose the physically-based (process) numerical models are typically utilized. However, in data-rich cases, one may use data-driven methods aiming at reconstructing the internal patterns of the modelled processes and relationships between the observed descriptive variables. This book focuses on data-driven modelling using methods of nonlinear dynamics and chaos theory. First, some fundamentals of physical oceanography, nonlinear dynamics and chaos, c |
Bibliography |
Includes bibliographical references and index |
Notes |
In English, with some Dutch |
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Print version record |
Subject |
Storm surges -- Methodology
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Storm surges -- Methodology
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Form |
Electronic book
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ISBN |
9781466553484 |
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1466553480 |
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