Predicting Storm Surges

  • Producent: Taylor
  • Oprawa: Miękka
Wysyłka: Niedostępna
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Opis: Predicting Storm Surges - Michael Siek

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, computational intelligence and European operational storm surge models are covered. After that a number of improvements in building chaotic models are presented: nonlinear time series analysis, multi-step prediction, phase space dimensionality reduction, techniques dealing with incomplete time series, phase error correction, finding true neighbours, optimization of chaotic model, data assimilation and multi-model ensemble prediction. The major case study is surge prediction in the North Sea, with some tests on a Caribbean Sea case. The modelling results showed that the enhanced predictive chaotic models can serve as an efficient tool for accurate and reliable short and mid-term predictions of storm surges in order to support decision-makers for flood prediction and ship navigation.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 RECOMMENDATIONS


Szczegóły: Predicting Storm Surges - Michael Siek

Tytuł: Predicting Storm Surges
Autor: Michael Siek
Producent: Taylor
ISBN: 9780415621021
Rok produkcji: 2011
Ilość stron: 200
Oprawa: Miękka
Waga: 1.2 kg


Recenzje: Predicting Storm Surges - Michael Siek

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Predicting Storm Surges

  • Producent: Taylor
  • Oprawa: Miękka

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, computational intelligence and European operational storm surge models are covered. After that a number of improvements in building chaotic models are presented: nonlinear time series analysis, multi-step prediction, phase space dimensionality reduction, techniques dealing with incomplete time series, phase error correction, finding true neighbours, optimization of chaotic model, data assimilation and multi-model ensemble prediction. The major case study is surge prediction in the North Sea, with some tests on a Caribbean Sea case. The modelling results showed that the enhanced predictive chaotic models can serve as an efficient tool for accurate and reliable short and mid-term predictions of storm surges in order to support decision-makers for flood prediction and ship navigation.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 RECOMMENDATIONS

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Cena 269,90 PLN
Nasza cena 254,60 PLN
Oszczędzasz 5%
Wysyłka: Niedostępna
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Szczegóły: Predicting Storm Surges - Michael Siek

Tytuł: Predicting Storm Surges
Autor: Michael Siek
Producent: Taylor
ISBN: 9780415621021
Rok produkcji: 2011
Ilość stron: 200
Oprawa: Miękka
Waga: 1.2 kg


Recenzje: Predicting Storm Surges - Michael Siek

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