Bio-Inspired Hybridization of Artificial Neural Networks: An Application for Mapping the Spatial Distribution of Soil Texture Fractions

Bio-Inspired Hybridization of Artificial Neural Networks: An Application for Mapping the Spatial Distribution of Soil Texture Fractions

Soil texture and particle size fractions (PSFs) are a critical characteristic of soil that influences most physical, chemical, and biological properties of soil; furthermore, reliable spatial predictions of PSFs are crucial for agro-ecological modeling. Here, series of hybridized artificial neural n...

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Bibliographic Details
Main Authors: Ruhollah Taghizadeh-Mehrjardi, Mostafa Emadi, Ali Cherati, Brandon Heung, Amir Mosavi, Thomas Scholten
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Remote Sensing
Subjects:
spatial distribution
particle size fractions
evolutionary algorithms
sub-humid regions
hybrid machine learning
artificial intelligence
Online Access:https://www.mdpi.com/2072-4292/13/5/1025

Internet

https://www.mdpi.com/2072-4292/13/5/1025

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