Artificial bee colony feature selection algorithm combined with machine learning algorithms to predict vertical and lateral distribution of soil organic matter in South Dakota, USA

Artificial bee colony feature selection algorithm combined with machine learning algorithms to predict vertical and lateral distribution of soil organic matter in South Dakota, USA

The main purpose of this study, is to evaluate an advanced feature selection technique, artificial bee colony (ABC) algorithm; to reduce the number of auxiliary variables derived from a digital elevation model (DEM) and remotely sensed data (e.g. Landsat images). A combination of depth functions (e....

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Bibliographic Details
Main Authors: Ruhollah Taghizadeh-Mehrjardi, Ram Neupane, Kunal Sood, Sandeep Kumar
Format: Article
Language:English
Published: Taylor & Francis Group 2017-05-01
Series:Carbon Management
Subjects:
digital soil mapping
auxiliary variables
support vector regression
artificial neural networks
south dakota
Online Access:http://dx.doi.org/10.1080/17583004.2017.1330593

Internet

http://dx.doi.org/10.1080/17583004.2017.1330593

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