التفاصيل البيبلوغرافية
| العنوان: |
Data fault detection algorithm based on multi-label classification in sensor network. (English) |
| المؤلفون: |
ZHANG Zhen-hai, LI Shi-ning, LI Zhi-gang, ZUO Xue-wen |
| المصدر: |
Application Research of Computers / Jisuanji Yingyong Yanjiu; Dec2014, Vol. 31 Issue 12, p3788-3817, 5p |
| مصطلحات موضوعية: |
DEBUGGING, CLASSIFICATION algorithms, SENSOR networks, DATA analysis, GENETIC algorithms, DATA reduction |
| مستخلص: |
Multiple data faults may occur at the same time in sensor network. In order to detect these data faults simultaneously, this paper modeled the data fault detection problem as a multi-label classification task. To improve the performance of multi-label classifiers in detecting data faults, it proposed a feature selection method based on multi-label ReliefF and genetic algorithm (MLRG). The method extended the ReliefF to the multi-label ReliefF which could estimate the quality of feature subset. MLRG firstly searched for a feature subset and then evaluated the feature subset using the multi-label ReliefF1. It performed experiments on the MLRG using three multi-label classifiers and compared it with other feature reduction algorithms. The experimental results show that MLRG can promote the performance of multi-label classifiers significantly in data faults detection. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
