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- W1502021839 abstract "Hail is one of the main meteorological disasters in our country, also it is the hot current research. The forecasting of hail is mostly used in the data return from radar. Based on radar return image, using the statistics of the K-means clustering algorithm and cellular neural networks (CNN) algorithm, processing the cloud image, and get the difference between the inside and outside layer outline. Compare the hail cloud image with the no hail cloud image to get the variance, we can find the difference of internal and external contours Using the hail cloud images and the no hail cloud image of Shihezi in Xinjiang province verification, validation of the conclusion of this paper is effective. Show that combined with K means clustering algorithm and CNN contour extraction algorithm to get the difference of internal and external contours is a effective method of forecasting the hail." @default.
- W1502021839 created "2016-06-24" @default.
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- W1502021839 date "2015-06-01" @default.
- W1502021839 modified "2023-09-23" @default.
- W1502021839 title "Based on K-Means Clustering and CNN Algorithm Research in Hail Cloud Determination" @default.
- W1502021839 cites W2030760038 @default.
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- W1502021839 doi "https://doi.org/10.1109/icmtma.2015.64" @default.
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