Can I read Combination of Effective Color Information and Machine Learning for Rapid Prediction of Soil Water Content on EtoBox?

Combination of Effective Color Information and Machine Learning for Rapid Prediction of Soil Water Content by Guanshi Liu; Shengkui Tian; Guofang Xu; Chengcheng Zhang; Mingxuan Cai is a Engineering article available to read on EtoBox.

What is Combination of Effective Color Information and Machine Learning for Rapid Prediction of Soil Water Content about?

Soil water content (SWC) is one of the critical indicators in various fields such as geotechnical engineering and agriculture. To avoid the time-consuming, destructive, and laborious drawbacks of conventional SWC measurements, the image-based SWC prediction is considered based on recent advances in quantitative soil color analysis. In this study, a promising method based on the Gaussian-fitting gray histogram is proposed for extracting characteristic parameters by analyzing soil images, aiming to alleviate the interference of complex surface conditions with color information extraction. In addition, an identity matrix consisting of 32 characteristic parameters from eight color spaces is constituted to describe the multi-dimensional information of the soil images. Meanwhile, a subset of 10 parameters is identified through three variable analytical methods. Then, four machine learning models for SWC prediction based on partial least squares regression (PLSR), random forest (RF), support vector machines regression (SVMR), and Gaussian process regression (GPR), are established using 32 and 10 characteristic parameters, and their performance is compared. The results show that the charac

Who reads Combination of Effective Color Information and Machine Learning for Rapid Prediction of Soil Water Content?

Author

Guanshi Liu; Shengkui Tian; Guofang Xu; Chengcheng Zhang; Mingxuan Cai

Publisher

Elsevier BV

Published

2023

Language

EN

Field

Engineering (Physical Sciences)