基于FCM的气温质量控制和专家场订正初步研究

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Abstract Aiming to improve the quality of ground temperature data in Anhui Province,the Fuzzy C-Means clustering algorithm is used in this paper to investigate quality control on temperature data.During the specific implementation process,similar clustering results of the area are outputted through FCM algorithm.The definition of stray rate (space scale) and the group velocity (time scale) of temperature can identify the outliers of temperature data.Further,outliers are corrected by using the method of fields of experts (FoEs),which have already considered the temperature information of adjacent and self station before and after the time.Compared with traditional methods,the algorithm is based on the overall temperature,which does not need to set the temperature reference value.FoEs can not only correct the outliers away from the group,but also can be used in interpolation processing for observational data that consecutive missing.The methods are more practical and scientific,which is suitable for calculating the temperature of large sample set.

Key words： temperature Fuzzy C-Means rate from the group group velocity FoEs model

Received: 09 February 2017

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	Liu Wenjing
	Liu Chengxiao
	Chen Hao
	Wang Gen

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Liu Wenjing,Liu Chengxiao,Chen Hao等. Preliminary study on temperature quality control and the fields of experts correction based on FCM[J]. Meteorological Hydrological and Marine Instrument, 2017, 34(2): 9-15.

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http://www.qxswhy.com/EN/ OR http://www.qxswhy.com/EN/Y2017/V34/I2/9

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