2023
DOI: 10.3390/rs15194681
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Research on Hyperspectral Modeling of Total Iron Content in Soil Applying LSSVR and CNN Based on Shannon Entropy Wavelet Packet Transform

Weichao Liu,
Hongyuan Huo,
Ping Zhou
et al.

Abstract: The influence of some seemingly anomalous samples on modeling is often ignored in the quantitative prediction of soil composition modeling with hyperspectral data. Soil spectral transformation based on wavelet packet technology only performs pruning and threshold filtering based on experience. The feature bands selected by the Pearson correlation coefficient method often have high redundancy. To solve these problems, this paper carried out a study of the prediction of soil total iron composition based on a new… Show more

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Cited by 3 publications
(1 citation statement)
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“…Particles move in the search space and search for better solutions by updating their speeds and positions continuously. The PSO algorithm has the characteristics of easy operation and fast convergence [22,23]. It has been extensively applied in various fields, such as function optimization, neural network training, pattern recognition, image processing, and so on.…”
Section: Pso-lssvr Modelmentioning
confidence: 99%
“…Particles move in the search space and search for better solutions by updating their speeds and positions continuously. The PSO algorithm has the characteristics of easy operation and fast convergence [22,23]. It has been extensively applied in various fields, such as function optimization, neural network training, pattern recognition, image processing, and so on.…”
Section: Pso-lssvr Modelmentioning
confidence: 99%