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Evolutionary polynomial regression model for the prediction of coastal dynamics

Conference Paper
Publication Date:
2016
abstract:
The effective protection of the coastal ecosystem requires a detailed knowledge of the morphological evolution of the coastal environment. Several probabilistic models have been developed in the last decades to implement a reliable statistical forecasting of coastline dynamics. In this work, the non-linear Evolutionary Polynomial Regression (EPR) model has been used for the first time to evaluate the short-term dynamics of the shoreline from a set of measured shoreline positions in previous years. A comparison of the mean known shoreline positions with those predicted by the model, together with their confidence and prediction intervals, can be used to assess the reliability of the estimation by the EPR model.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
EPR; prediction; coastal dynamics; genetic algorithm; genetic programming; evolutionary computation; Coastal dynamics; Evolutionary polynomial regression; Marine regression/transgression; Multilinear regression
List of contributors:
Passarella, Giuseppe; Barca, Emanuele; Maggi, Sabino; Bruno, DELIA EVELINA
Authors of the University:
BARCA EMANUELE
BRUNO DELIA EVELINA
MAGGI SABINO
PASSARELLA GIUSEPPE
Handle:
https://iris.cnr.it/handle/20.500.14243/322224
Book title:
Proceedings of 6th EnvImeko IMEKO TC19 Second Edition: Workshop on Environmental Instrumentation and Measurements
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