A Fuzzy C-Means Clustering Algorithm and Application in Meteorological Data

The fuzzy clustering algorithm is sensitive to the m value and the degree of membership. Because of the deficiencies of traditional FCM clustering algorithm and we also made specific improvement methods. Through the calculation of the value of m, the amendments of degree of membership to the discussion of issues, effectively compensate for the deficiencies of the traditional algorithm and achieve a relatively good clustering effect. Finally, through the analysis of temperature observation data of the three northeastern province of china in 2000, verify the reasonableness of the method.