Concrete Compression Test Data Estimation Based on a Wavelet Neural Network Model
Joint Authors
Wang, Haiying
Wang, Xinping
Wang, Chao
Xu, Jian
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-02-11
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Firstly, a genetic algorithm (GA) and simulated annealing (SA) optimized fuzzy c-means clustering algorithm (FCM) was proposed in this paper, which was developed to allow for a clustering analysis of the massive concrete cube specimen compression test data.
Then, using an optimized error correction time series estimation method based on the wavelet neural network (WNN), a concrete cube specimen compressive strength test data estimation model was constructed.
Taking the results of cluster analysis as data samples, the short-term accurate estimation of concrete quality was carried out.
It was found that the mean absolute percentage error, e1, and the root mean square error, e2, for the samples were 6.03385% and 3.3682KN, indicating that the proposed method had higher estimation accuracy and was suitable for concrete compressive test data short-term quality estimations.
American Psychological Association (APA)
Wang, Haiying& Wang, Xinping& Wang, Chao& Xu, Jian. 2019. Concrete Compression Test Data Estimation Based on a Wavelet Neural Network Model. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1195859
Modern Language Association (MLA)
Wang, Haiying…[et al.]. Concrete Compression Test Data Estimation Based on a Wavelet Neural Network Model. Mathematical Problems in Engineering No. 2019 (2019), pp.1-10.
https://search.emarefa.net/detail/BIM-1195859
American Medical Association (AMA)
Wang, Haiying& Wang, Xinping& Wang, Chao& Xu, Jian. Concrete Compression Test Data Estimation Based on a Wavelet Neural Network Model. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1195859
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1195859