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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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| Udgivet i: | Sensors (Basel) |
|---|---|
| Main Authors: | , , , , , , |
| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
MDPI
2020
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| Fag: | |
| Online adgang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7582716/ https://ncbi.nlm.nih.gov/pubmed/33008132 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s20195609 |
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