Hyper-Spectral Estimation Model of Soil Organic Matter Based on Generalized Greyness of Grey Number
The Journal of Grey System ›› 2022, Vol. 34 ›› Issue (2): 22-40.
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Abstract:
Due to the complexity of society and the high degree of uncertainty of the issues faced, precise numbers are, in many cases, difficult to describe their nature. And to deal with the problem that the existing interval grey number distance method does not reflect the characteristics of interval grey number well. This paper introduces a distance entropy to assign different weights to the upper and lower bounds and the kernel. To prevent the extreme value bias of the grey correlation coefficients, we propose a relative weight to constrain the extreme values. Considering the loss aversion of decision-makers, an extended TODIM is proposed, which combines the corresponding gains and losses to obtain the perceived dominance degree. From the method proposed in this paper, the perceived dominance degree is established to provide the ranking of the decision alternatives. A case of selecting an artillery weapon for a certain unit is used to validate the proposed method, followed by a comparative analysis.
Key words: Soil Organic Matter, Hyper-spectral Remote Sensing, Interval Grey Number, Generalized Greyness, Spectral Estimation
Wenjing Ren, Xican Li, Jieya Liu, Tianzi Ding.
Hyper-Spectral Estimation Model of Soil Organic Matter Based on Generalized Greyness of Grey Number [J]. The Journal of Grey System, 2022, 34(2): 22-40.
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URL: https://jgrey.nuaa.edu.cn/EN/
https://jgrey.nuaa.edu.cn/EN/Y2022/V34/I2/22