Research on Outlier Detection Algorithm for Evaluation of Battery System Safety
Research on Outlier Detection Algorithm for Evaluation of Battery System Safety
复制标题
电池系统安全评价异常值检测算法研究
DOI:
10.1155/2014/830402
复制
发表时间:
2014-01
影响因子:
2.1
通讯作者:
Sheng Lu
中科院分区:
文献类型:
--
作者:
Changhao Piao;Zhi Huang;Ling Su;Sheng Lu
Battery system is the key part of the electric vehicle. To realize outlier detection in the running process of battery system effectively, a new high-dimensional data stream outlier detection algorithm (DSOD) based on angle distribution is proposed. First, in order to improve the algorithm stability in high-dimensional space, the method of angle distribution-based outlier detection algorithm is employed. Second, to reduce the computational complexity, a small-scale calculation set of data stream is established, which is composed of normal set and border set. For the purpose of solving the problem of concept drift, an update mechanism for the normal set and border set is developed in this paper. By this way, these hidden abnormal points will be rapidly detected. The experimental results on real data sets and battery system simulation data sets demonstrate that DSOD is more efficient than Simple variance of angles (Simple VOA) and angle-based outlier detection (ABOD) and is very suitable for the evaluation of battery system safety.
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DOI:
--
发表时间:
2010
期刊:
Journal of Chongqing University of Posts and Telecommunications
影响因子:
--
作者:
Gou Guang-le
通讯作者:
Gou Guang-le
DOI:
--
发表时间:
1998-08
期刊:
--
影响因子:
--
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影响因子:
4.3
作者:
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通讯作者:
Jiang, W
DOI:
--
发表时间:
2012
期刊:
Journal of the Automotive Safety and Energy
影响因子:
--
作者:
Li Zhe
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影响因子:
15.9
作者:
iovanni Stracquadanio;Giuseppe Nicosia
通讯作者:
iovanni Stracquadanio;Giuseppe Nicosia