Evolutionary Polynomial Regression Model for the Prediction of Coastal Dynamics

D. E. Bruno, E. Barca, R. M. Goncalves, A. Lay-Ekuakille, S. Maggi, G. Passarella
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.
Keywords:
evolutionary polynomial regression, multilinear regression, coastal dynamics, marine regression/transgression
Download:
IMEKO-TC19-2016-022.pdf
DOI:
-
Event details
IMEKO TC:
TC19
Event name:
Measurement for the endorsement of the subsoil and historical evidences
Title:

6th EnvIMEKO - Symposium on Environmental Instrumentation and Measurements

Place:
Reggio Calabria, ITALY
Time:
24 June 2016 - 25 June 2016