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Soil pH value grey relation estimation model based on hyper-spectral

Soil pH value grey relation estimation model based on hyper-spectral The purpose of this paper is to establish the grey relational estimating model of soil pH value based on hyper-spectral data.Design/methodology/approachAs to the uncertainty of the factors affecting the soil pH value estimation based on hyper-spectral, the grey weighted relation estimation model was set up according to the grey system theory. Then the linear regression correction model is established according to the difference and grey relation degree information between the estimated samples and their corresponding pattern. At the same time, the model was applied to Hengshan county of Shanxi province.FindingsThe results are convincing: not only that the linear regression correction model of grey relation estimating pattern of soil pH value based on hyper-spectral data is valid, but also the model’s estimating accuracy is higher, which the corrected average relative error is 0.2578 per cent, and the decision coefficient R2=0.9876.Practical implicationsThe method proposed in the paper can be used at soil pH value hyper-spectral inversion and even for other similar forecast problem.Originality/valueThe paper succeeds in realising both the soil pH value hyper-spectral grey relation estimating pattern based on the grey relational theory and the correction model of the estimating pattern by using the linear regression. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Grey Systems: Theory and Application Emerald Publishing

Soil pH value grey relation estimation model based on hyper-spectral

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
2043-9377
DOI
10.1108/gs-05-2018-0027
Publisher site
See Article on Publisher Site

Abstract

The purpose of this paper is to establish the grey relational estimating model of soil pH value based on hyper-spectral data.Design/methodology/approachAs to the uncertainty of the factors affecting the soil pH value estimation based on hyper-spectral, the grey weighted relation estimation model was set up according to the grey system theory. Then the linear regression correction model is established according to the difference and grey relation degree information between the estimated samples and their corresponding pattern. At the same time, the model was applied to Hengshan county of Shanxi province.FindingsThe results are convincing: not only that the linear regression correction model of grey relation estimating pattern of soil pH value based on hyper-spectral data is valid, but also the model’s estimating accuracy is higher, which the corrected average relative error is 0.2578 per cent, and the decision coefficient R2=0.9876.Practical implicationsThe method proposed in the paper can be used at soil pH value hyper-spectral inversion and even for other similar forecast problem.Originality/valueThe paper succeeds in realising both the soil pH value hyper-spectral grey relation estimating pattern based on the grey relational theory and the correction model of the estimating pattern by using the linear regression.

Journal

Grey Systems: Theory and ApplicationEmerald Publishing

Published: Sep 24, 2018

Keywords: Grey relation degree; Hyper-spectral; Modified model; Soil pH value; Spectral estimation

References