Application of Data Denoising and Classification Algorithm Based on RPCA and Multigroup Random Walk Random Forest in Engineering
Joint Authors
Wang, Renchao
Wang, Yanlei
Ma, Yuming
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-12-24
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
Data classification algorithms are often used in the engineering field, but the data measured in the actual engineering often contains different types and degrees of noise, such as vibration noise caused by water flow when measuring the natural frequencies of aqueducts or other hydraulic structures, which will affect the accuracy of classification.
In reality, these noises often appear disorganized and stochastic and some existing algorithms exhibit poor performance in the face of these non-Gaussian noise.
Therefore, the classification algorithms with excellent performance are needed.
To address this issue, a hybrid algorithm of robust principal component analysis (RPCA) combined multigroup random walk random forest (MRWRF) is proposed in this paper.
On the one hand RPCA can effectively remove part of non-Gaussian noise, and on the other hand MRWRF can select a better number of decision trees (DTs), which can effectively improve random forest (RF) robustness and classification performance, and the combination of RPCA and MRWRF can effectively classify data with non-Gaussian distribution noise.
Compared with other existing algorithms, this hybrid algorithm has strong robustness and preferable classification performance and can thus provide a new approach for data classification problems in engineering.
American Psychological Association (APA)
Wang, Renchao& Wang, Yanlei& Ma, Yuming. 2019. Application of Data Denoising and Classification Algorithm Based on RPCA and Multigroup Random Walk Random Forest in Engineering. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1196967
Modern Language Association (MLA)
Wang, Renchao…[et al.]. Application of Data Denoising and Classification Algorithm Based on RPCA and Multigroup Random Walk Random Forest in Engineering. Mathematical Problems in Engineering No. 2019 (2019), pp.1-15.
https://search.emarefa.net/detail/BIM-1196967
American Medical Association (AMA)
Wang, Renchao& Wang, Yanlei& Ma, Yuming. Application of Data Denoising and Classification Algorithm Based on RPCA and Multigroup Random Walk Random Forest in Engineering. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1196967
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1196967