期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2015
卷号：8
期号：12
页码：181-190
DOI：10.14257/ijhit.2015.8.12.12
出版社：SERSC
摘要：An approach based on online RBFNN is proposed to predict the ball - carrier's behavior shooting, passing and dribbling in basketball matches. In order to describe the factors affecting the behavior of ball carrier, artificial potential field (APF)-based player information is introduced to model the court situation of all players after tracking and vision range determination, then a feature vector is formed as the input of the online RBF neural network. The behavior prediction of the ball carrier is solved by the online RBF neural network based on GIRAN learning algorithm. Compared with the offline RBF neural network, the online neural network can adjust both structure and parameters to basketball matches, thus the prediction accuracy is improved to some extent.
