Predicting Storm Surges : Chaos, Computational Intelligence, Data Assimilation and Ensembles - Info and Reading Options
UNESCO-Ihe PhD Thesis
By Michael Siek
"Predicting Storm Surges : Chaos, Computational Intelligence, Data Assimilation and Ensembles" was published by Taylor & Francis Group in 2013 - Hoboken, it has 239 pages and the language of the book is English.
“Predicting Storm Surges : Chaos, Computational Intelligence, Data Assimilation and Ensembles” Metadata:
- Title: ➤ Predicting Storm Surges : Chaos, Computational Intelligence, Data Assimilation and Ensembles
- Author: Michael Siek
- Language: English
- Number of Pages: 239
- Publisher: Taylor & Francis Group
- Publish Date: 2013
- Publish Location: Hoboken
“Predicting Storm Surges : Chaos, Computational Intelligence, Data Assimilation and Ensembles” Subjects and Themes:
- Subjects: Storm surges - Methodology - Ondes de tempête - Méthodologie
Edition Identifiers:
- The Open Library ID: OL33442396M - OL21552895W
- ISBN-13: 9781280123078 - 9780415621021
- All ISBNs: 9781280123078 - 9780415621021
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"Predicting Storm Surges : Chaos, Computational Intelligence, Data Assimilation and Ensembles" Description:
Open Data:
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
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