Abstract: In view of the defects that the prediction accuracy of the existing position prediction method is low and a large number of historical movement path data need to be relied on in mobile wireless sensor network,this paper proposed an A-USVC position prediction method based on uncertain supporting vector machines.This method uses the node membership vector collected by nodes to construct classification prediction model.On the basis of the constructed prediction model and the calculated moving deflecting direction of mobile node,the location of unknown node is determined.Therefore,the position of unknown mobile node can be predicted.The simulation tests show that the proposed method improves the accuracy by 35% compared with the traditional Markov model prediction method,and improves the accuracy by 19% compared with the neural network prediction method.The A-USVC position prediction method can improve the position prediction accuracy effectively,which has low computational complexity and can also maintain good prediction ability in the case of small samples.

Key words: Mobile wireless sensor network, Node membership vector, Position prediction, Uncertain support vector machines