Tao Li1, Xiang Li1, *, Yongjun Ren2, Jinyue Xia3
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 621-631, 2020, DOI:10.32604/cmc.2020.06463
Abstract In view of the low accuracy of traditional ground nephogram recognition
model, the authors put forward a k-means algorithm-acquired neural network ensemble
method, which takes BP neural network ensemble model as the basis, uses k-means
algorithm to choose the individual neural networks with partial diversities for integration,
and builds the cloud form classification model. Through simulation experiments on
ground nephogram samples, the results show that the algorithm proposed in the article
can effectively improve the Classification accuracy of ground nephogram recognition in
comparison with applying single BP neural network and traditional BP AdaBoost
ensemble algorithm on classification of ground nephogram. More >
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