Prediction of Moving Objects' K-Nearest Neighbor Based on Fuzzy-Rough Sets Theory
Xiaoguang Hong, Yan Yuan, Xinglei Hu · 2007
In the previous study of the prediction of moving objects' k-nearest neighbor, there are many analyses on the diversified uncertainties of objects' predicted position and many disposals, but there have not been any measures to deal with the rough-uncertainty of moving objects' k-nearest neighbor, which is caused by the fuzzy-uncertainty of moving objects' predicted position. In this paper, the theory of fuzzy-rough sets is employed to analyze the fuzzy position of moving objects and its extended k + m nearest neighbor. Also, the fuzzy-rough membership function is employed to obtain the final k-nearest neighbor. A comparison between the processed result and the initial result is made by experiments. It is concluded that, compared to the actual position of moving objects, the analysis based on the theory of fuzzy-rough sets can promote the precision of its k-nearest neighbor noticeably.