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Book Cover
E-book
Author Siek, Michael

Title Predicting Storm Surges : Chaos, Computational Intelligence, Data Assimilation and Ensembles
Published Hoboken : CRC Press, 2011

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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
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
Print version record
Subject Storm surges -- Methodology
Storm surges -- Methodology
Form Electronic book
ISBN 9781466553484
1466553480