所属单位：计算机科学与技术学院/人工智能学院/软件学院
发表刊物：Jisuanji Yanjiu yu Fazhan
摘要：Multi-objective optimization is one of the key technologies in moving objects data management. While in the procession of multi-objective optimization query, the concerned target object's attributes may depend on the other moving objects' attributes. Therefore, moving objects can affect each other, which will lead to the uncertainty of the object's properties. The existing multi-objective optimization algorithms need to traverse all the target objects, furthermore, they can't effectively solve the problem of dynamic change of object attributes. We propose an effective multi-objective optimization algorithm DSP-Topk (dynamic and support pruning Topk) to solve the query in the obstacle space. Visual area model can calculate the distance between the moving objects with obstacles. The method of viewable area which applies the maximum differential angle can improve the calculation performance of the distance between moving objects. Then, we study the uncertainty of the object's attributes by using the dynamic adjustment mechanism. The given pruning strategy with preprocessing improves the efficiency of the query. The results of experiments indicate that DSP-Topk algorithm improves the query efficiency significantly compared with the existing Topk algorithm and DS-Topk algorithm. Combined with the real testing data of goods in stores, the rationality and effectiveness of the algorithm are also verified. © 2017, Science Press. All right reserved.
ISSN号：1000-1239
是否译文：否
发表时间：2017-03-01
合写作者：F70206551,Li, Dongjing,许建秋,夏冰,秦小麟
通讯作者：李博涵
发表时间：2017-03-01