Novel Ensemble Approach of Deep Learning Neural Network (DLNN) Model and Particle Swarm Optimization (PSO) Algorithm for Prediction of Gully Erosion Susceptibility

This study aims to evaluate a new approach in modeling gully erosion susceptibility (GES) based on a deep learning neural network (DLNN) model and an ensemble particle swarm optimization (PSO) algorithm with DLNN (PSO-DLNN), comparing these approaches with common artificial neural network (ANN) and...

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Principais autores:	Shahab S. Band, Saeid Janizadeh, Subodh Chandra Pal, Asish Saha, Rabin Chakrabortty, Manouchehr Shokri, Amirhosein Mosavi
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2020-09-01
Series:	Sensors
Assuntos:	gully erosion susceptibility deep learning neural network DLNN particle swarm optimization PSO geohazard
Acceso en liña:	https://www.mdpi.com/1424-8220/20/19/5609
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