基于模糊-粗糙集的移动对象k近邻预测

已往移动对象k近邻预测的研究中,有各种不确定性的分析以及对象本身预测位置不确定性的处理,而预测位置模糊不确定性导致其k近邻查询边界的粗糙不确定性的相关处理仍是空白.本文应用模糊一粗糙集的理论,先分析了已有方法得出的预测位置的模糊性,再用传统方法求得基于预测位置的扩展k m近邻集,最后借助模糊一粗糙隶属函数来最终确定所求k近邻集合中的各个点.实验数据表明,本方法明显提高了k近邻集合相对移动对象实际位置的精确度.

Fuzzy-Rough Sets for Prediction of Moving Objects' K-Nearest Neighbor

There are many analyses on the diversified uncertainty and many disposals on the uncertainty of objects' predicted position in the previous study of the prediction of moving objects' k-nearest neighbor.But there have not been any measure to deal with the rough-uncertainty of moving objects' k-nearest neighbor set,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 the moving objects and its extended k m nearest neighbor set.Also,the fuzzy-rough membership function is employed to obtain thefinal k-nearest neighbor set.A comparison between the processed result and the initial result is made by experiments.Compared to the actual position of the moving objects,the analysis based on the theory of fuzzy-rough sets can promote the precision of its k-nearest neighbor set distinctly.