期刊
MATHEMATICAL PROBLEMS IN ENGINEERING
卷 2014, 期 -, 页码 -出版社
HINDAWI LTD
DOI: 10.1155/2014/763469
关键词
-
资金
- NSFC [61271376, 51308115, 91120010]
- National Basic Research Program of China (973 Program) [2012CB725405]
- Beijing Natural Science Foundation [4122067]
There are increasing concerns about missing traffic data in recent years. In this paper, a robust missing traffic flow data imputation approach based on matrix completion is proposed. In the proposed method, the similarity of traffic flow from day to day is exploited to impute missing data by the low-rank hypothesis of constructed traffic flow matrix. And the physical limitation of road capacity and nonnegativity is also considered through the optimization process, which avoids the possibility of producing negative and overcapacity values. Moreover, the proposed algorithm can impute missing data and recover outlier in a unify framework. The experiment results show that the proposed method is more accurate, stable, and reasonable.
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