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Li J.-M.,Meteorological Technology Equipment Center | Li J.-M.,Key Laboratory of Meteorology and Ecological Environment | Han L.,Meteorological Technology Equipment Center | Zhen S.-Y.,Meteorological Technology Equipment Center | Yao L.-T.,Meteorological Technology Equipment Center
Advances in Intelligent and Soft Computing | Year: 2011

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. © 2011 Springer-Verlag Berlin Heidelberg. Source


Li J.-M.,Meteorological Technology Equipment Center | Li J.-M.,Key Laboratory of Meteorology and Ecological Environment | Han L.,Meteorological Technology Equipment Center | Zhen S.-Y.,Meteorological Technology Equipment Center | Yao L.-T.,Meteorological Technology Equipment Center
Advances in Intelligent and Soft Computing | Year: 2011

The utilize of GStar-I soil moisture content viewer has greatly changed the information management of meteorological departments, the accuracy of the equipment is a big problem. Checking the possible malfunction of the equipment from the collected data intelligently is a solution. DBSCAN algorithm is a clustering algorithm, which can help to discover the noise points help to classify the noise points can analyze the reason of malfunction. © 2011 Springer-Verlag Berlin Heidelberg. Source

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