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Soil moisture prediction with feature selection using a neural network

Song, Junlei; Wang, Dianhong; Liu, Nianjun; Cheng , Li; Du, Lan; Zhang, Ke


For the problem of soil moisture prediction, existing approaches in literature [6, 11] usually utilize as many decision factors as possible, e.g. rainfall, solar irradiance, drainage, etc. However, the redundancy aspect of the decision factors has not been studied rigorously. Previous research work in data mining has shown that removing redundant features improves rather than deteriorates the prediction accuracy. In this paper, we propose an approach to the problem of soil moisture prediction,...[Show more]

CollectionsANU Research Publications
Date published: 2008
Type: Conference paper
Source: Proceedings of Digital Image Computing: Techniques and Applications (DICTA 2008)
DOI: 10.1109/DICTA.2008.35


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07_Song_Soil_moisture_prediction_with_2008.pdf289.02 kBAdobe PDF    Request a copy

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