Neural networks and sea time series : reconstruction and extreme event analysis This self contained book is devoted to the application of neural networks to the concrete problem of handling the time series of sea data i.e. significant wave heights and sea levels. Beginning with an explanation of neural networks fundamentals for beginners the authors follow with a review of general statements and rigorous facts and conclude with applications and algorithms for particular data sets having well defined parameters. Specifically analyzed are the time series of measures observed from a system of sea buoys as well as the reconstruction of missing values that are largely present in these time series. Neural networks are used to solve this problem and the reconstructed time series are modeled to estimate the probability of large events using extreme value theory. This ability to model and estimate is important for the construction of sea structures ports and marine experiments. Neural Networks and Sea Time Series is a unique monograph on the topic and may stimulate new research and results in the field. The book will be a useful resource for a diverse audience of graduate students researchers and practitioners in applied mathematics data analysis meteorology hydraulic civil and marine engineering. TOC:* Introduction * Penomenology of the Waves and Tides * Models of Waves and Tides * Artificial Neural Networks * Approximation Theory * Ectreme Value Theory * Application of ANN to Sea Time Series * Application of Approximation theory and ARMA models * Neural Networks and Extreme Events * Other Stations around Italy American Buoys * Temperatures Precipitations Geological Maps * References * Index