Predicting Storm Surges: Chaos, Computational Intelligence, Data Assimilation and Ensembles: Unesco-Ihe PhD Thesis

ISBN-13: 9781138475236 / Angielski / Twarda / 2017

Michael Siek

Opis

Some children seem different, detached, disinterested in the games of other children. They prefer their hobbies to friends of their own age and if forced into community activities, as they often are at school, can become aggressive and difficult. In Loners, Sula Wolff describes a childhood personality syndrome that has frequently been neglected. Often using children's own words, their lives and problems become real as she unwraps their stories from first referral to adulthood. Some have become talented and successful adults, whilst others are less fortunate in later years. Carefully documented and meticulously researched, this study makes compelling reading.

Spis treści

CHAPTER 1: INTRODUCTION CHAPTER 2: CASE STUDY CHAPTER 3: STORM SURGE MODELINGCHAPTER 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 OPTIMALPREDICTIVE CHAOTIC MODEL CHAPTER 9: REAL-TIME DATA ASSIMILATION USING NARX NEURAL NETWORK CHAPTER 10: ENSEMBLE MODEL PREDICTION CHAPTER 11: CONCLUSIONS AND RECOMMENDATIONS

O autorze

Michael Siek earned his B.Sc.degree in Mathematics from Airlangga University and B.Com. degree in Information Management from STIKOM Institute, both in 2000 and M.Sc. degree in Hydroinformatics from UNESCO-IHE, The Netherlands in 2003. He received his Ph.D. degree in Hydroinformatics from Delft University of Technology (TUDelft) and UNESCO-IHE in 2011 with the thesis entitled Predicting storm surges: chaos, computational intelligence, data assimilation, ensembles. Previously, he worked as a full-time lecturer at University of Surabaya and a visiting lecturer at Petra Christian University in the Faculty of Engineering and Faculty of Economics. His research has spanned a large number of disciplines, emphasizing data-driven and physically-based modelling, hydrological and coastal modelling, nonlinear dynamics and chaos theory, computational intelligence, optimization techniques, data mining, data assimilation, multi-model ensemble predictions with a wide range of real-life applications.