The prediction of landslide displacements is an important issue for the management of areas characterized by a high susceptibility to geomorphological hazards. The increased availability of monitoring data, like inclinometric measures, piezometric levels, encourages the development of prediction techniques and among these the use of data-driven models. This work introduces the use of an evolutionary modeling technique, namely EPRMOGA to model the relationship between the expected displacements and the past measured values of displacements and past cumulative rainfall values.
Predicting Landslide Displacements by Multi-objective Evolutionary Polynomial Regression / Doglioni, Angelo; Crosta, Giovanni B.; Frattini, Paolo; Melidoro, Nicola Luigi; Simeone, Vincenzo - In: Engineering Geology for Society and Territory. Volume 5 : Urban Geology, Sustainable Planning and Landscape Exploitation / [a cura di] Giorgio Lollino, Andrea Manconi, Fausto Guzzetti, Martin Culshaw, Peter Bobrowsky, Fabio Luino. - STAMPA. - Cham, CH : Springer, 2015. - ISBN 978-3-319-09047-4. - pp. 651-654 [10.1007/978-3-319-09048-1_127]
Predicting Landslide Displacements by Multi-objective Evolutionary Polynomial Regression
Angelo Doglioni;Melidoro, Nicola Luigi;Vincenzo Simeone
2015-01-01
Abstract
The prediction of landslide displacements is an important issue for the management of areas characterized by a high susceptibility to geomorphological hazards. The increased availability of monitoring data, like inclinometric measures, piezometric levels, encourages the development of prediction techniques and among these the use of data-driven models. This work introduces the use of an evolutionary modeling technique, namely EPRMOGA to model the relationship between the expected displacements and the past measured values of displacements and past cumulative rainfall values.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
