Scheda di dettaglio – i prodotti della ricerca
| Dato | Valore |
|---|---|
| Title | Evolutionary polynomial regression model for the prediction of coastal dynamics |
| 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. |
| Source | 6th EnvImeko IMEKO TC19 Second Edition Workshop on Environmental Instrumentation and Measurements, Reggio Calabria, Italy, 28/10/2016 |
| Keywords | EPRpredictioncoastal dynamicsgenetic algorithmgenetic programmingevolutionary computationCoastal dynamicsEvolutionary polynomial regressionMarine regression/transgressionMultilinear regression |
| Year | 2016 |
| Type | Contributo in atti di convegno |
| Authors | Bruno, D. E.; Barca, E.; Goncalves, R. M.; Lay-Ekuakille, A.; Maggi, S.; Passarella, G. |
| Text | 362478 2016 Scopus 2 s2.0 85022027226 EPR prediction coastal dynamics genetic algorithm genetic programming evolutionary computation Coastal dynamics Evolutionary polynomial regression Marine regression/transgression Multilinear regression Evolutionary polynomial regression model for the prediction of coastal dynamics Bruno, D. E.; Barca, E.; Goncalves, R. M.; Lay Ekuakille, A.; Maggi, S.; Passarella, G. CNR IRSA, Water Research Institute, Bari, Italy; Department of Cartography Engineering, Federal University of Pernambuco, Recife, Brazil; Department of Innovation Engineering, Universita del Salento, Lecce, Italy 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. Proceedings of 6th EnvImeko IMEKO TC19 Second Edition Workshop on Environmental Instrumentation and Measurements Morello, Rosario; Fillanoti, Pasquale 978 15 108281 2 4 Published version http //www.scopus.com/record/display.url eid=2 s2.0 85022027226 origin=inward 2016 January 6th EnvImeko IMEKO TC19 Second Edition Workshop on Environmental Instrumentation and Measurements Reggio Calabria, Italy 28/10/2016 Internazionale Su invito Bruno et al., Evolutionary Polynomial Regression Model for the Prediction of Coastal Dynamics IMEKO TC19 2016 022.pdf Contributo in atti di convegno giuseppe.passarella PASSARELLA GIUSEPPE emanuele.barca BARCA EMANUELE sabino.maggi MAGGI SABINO deliaevelina.bruno BRUNO DELIA EVELINA TA.P04.005.008 Integrazione di metodologie per il monitoraggio e la modellizzazione per la gestione delle risorse idriche |