Abstract
The error detection of soil moisture content viewer is a hot topic to meteorological departments, this paper introduces a soil moisture content error data detection system to detect the broken devices, support vector machines theory is used to be the classifier to detect the error device from the collected data. The structure of the system is also introduced in this paper. The experiments have shown its feasibility.
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References
Zhu, J., Li, R., Wu, S.: An effective algorithm for inverse problem of SVM based on MM algorithm. In: Proceedings of the IEEE International Conference on Machine learning and Cybernetics, vol. (2), pp. 1000–1004 (2009)
Tang, Y., He, Y., Krasser, S.: Highly Scalable SVM Modeling with Random Granulation for Spam Sender Detection. In: Proc. of The Seventh International Conference on Machine Learning and Applications (ICMLA 2008), pp. 659–664 (2008)
Drucker, H., Wu, D., Vapnik: Support vector machines for spam categorization. IEEE Transactions on Neural Networks 20(5), 1048–1054 (1999)
Hao, P.-Y., Chiang, J.-H., Tu, Y.-K.: Hierarchically SVM classification based on support vector clustering method and its application to document categorization. Expert Systems with Applications (33), 627–635 (2007)
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© 2011 Springer-Verlag Berlin Heidelberg
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Li, JM., Han, L., Zhen, SY., Yao, LT. (2011). Error Detection Technique for Soil Moisture Content Viewer. In: Jin, D., Lin, S. (eds) Advances in Computer Science, Intelligent System and Environment. Advances in Intelligent and Soft Computing, vol 106. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23753-9_24
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DOI: https://doi.org/10.1007/978-3-642-23753-9_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23752-2
Online ISBN: 978-3-642-23753-9
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