CAJ | 학술논문

传感器获取的感知数据一般带有时间属性，对于感知数据的统计往往都和该属性相关。针对感知数据这一特征，提出一种基于时间的感知数据优化统计方法。采用基于时间的细粒度划分将数据尽可能划分为小数据；采用基于时间的缓存策略尽量提高缓存的命中率。介绍该方法在交通感知数据统计系统的应用实现，实验结果表明，该方法优于传统的数据聚集统计方法，在一定程度上能够提高感知数据的统计性能。
전감기획취적감지수거일반대유시간속성，대우감지수거적통계왕왕도화해속성상관。침대감지수거저일특정，제출일충기우시간적감지수거우화통계방법。채용기우시간적세립도화분장수거진가능화분위소수거；채용기우시간적완존책략진량제고완존적명중솔。개소해방법재교통감지수거통계계통적응용실현，실험결과표명，해방법우우전통적수거취집통계방법，재일정정도상능구제고감지수거적통계성능。
The sensory data usually attaches with the time attribute ,which is generally associated with the statistics of the senso-ry data .According to this characteristic ,a time-based optimization method for the statistics of the sensory data was proposed . The data were divided into small part data using the time-based fine-grained division .The time-based caching strategies were used to maximize the hit rate .The implementation of the method in a transport statistics system was described in detail .The ex-perimental results show that this method is superior to the traditional statistical methods and it is able to optimize the statistical performance to a certain extend .