A Bidirectional Searching Strategy to Improve Data Quality Based on K-Nearest Neighbor Approach
作者： Minghui Ma , Shidong Liang , Yifei Qin
DOI: 10.3390/SYM11060815
关键词:
摘要: Traffic data are the basis of traffic control, planning, management, and other implementations. Incomplete that not conducive to all aspects transport research related activities can have adverse effects such as status identification error poor control performance. For intelligent transportation systems, recovery strategy has become increasingly important since application system relies on quality. In this study, a bidirectional k-nearest neighbor searching was constructed for effectively detecting recovering abnormal considering symmetric time network correlation in dimension. Moreover, state vector proposed designed based retrieval enhancing accuracy. addition, shows significantly more accuracy compared those previous methods.
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