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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Detalles Bibliográficos
Autores principales: Band, Shahab S., Janizadeh, Saeid, Chandra Pal, Subodh, Saha, Asish, Chakrabortty, Rabin, Shokri, Manouchehr, Mosavi, Amirhosein
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7582716/
https://www.ncbi.nlm.nih.gov/pubmed/33008132
http://dx.doi.org/10.3390/s20195609

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7582716/
https://www.ncbi.nlm.nih.gov/pubmed/33008132
http://dx.doi.org/10.3390/s20195609

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