A Novel Prediction Model for Car Body Vibration Acceleration Based on Correlation Analysis and Neural Networks
This paper aims to create a prediction model for car body vibration acceleration that is reliable, effective, and close to real-world conditions. Therefore, a huge amount of data on railway parameters were collected by multiple sensors, and different correlation coefficients were selected to screen...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2018/1752070 |
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| _version_ | 1832565459867664384 |
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| author | Shubin Zheng Qianwen Zhong Xiaodong Chai Xingjie Chen Lele Peng |
| author_facet | Shubin Zheng Qianwen Zhong Xiaodong Chai Xingjie Chen Lele Peng |
| author_sort | Shubin Zheng |
| collection | DOAJ |
| description | This paper aims to create a prediction model for car body vibration acceleration that is reliable, effective, and close to real-world conditions. Therefore, a huge amount of data on railway parameters were collected by multiple sensors, and different correlation coefficients were selected to screen out the parameters closely correlated to car body vibration acceleration. Taking the selected parameters and previous car body vibration acceleration as the inputs, a prediction model for car body vibration acceleration was established based on several training algorithms and neural network structures. Then, the model was successfully applied to predict the car body vibration acceleration of test datasets on different segments of the same railway. The results show that the proposed method overcomes the complexity and uncertainty of the multiparameter coupling analysis in traditional theoretical models. The research findings boast a great potential for application. |
| format | Article |
| id | doaj-art-93cccb6ef95e4652a8a9028a7dcdadaa |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-93cccb6ef95e4652a8a9028a7dcdadaa2025-02-03T01:07:48ZengWileyJournal of Advanced Transportation0197-67292042-31952018-01-01201810.1155/2018/17520701752070A Novel Prediction Model for Car Body Vibration Acceleration Based on Correlation Analysis and Neural NetworksShubin Zheng0Qianwen Zhong1Xiaodong Chai2Xingjie Chen3Lele Peng4School of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai 201620, ChinaSchool of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai 201620, ChinaSchool of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai 201620, ChinaSchool of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai 201620, ChinaSchool of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai 201620, ChinaThis paper aims to create a prediction model for car body vibration acceleration that is reliable, effective, and close to real-world conditions. Therefore, a huge amount of data on railway parameters were collected by multiple sensors, and different correlation coefficients were selected to screen out the parameters closely correlated to car body vibration acceleration. Taking the selected parameters and previous car body vibration acceleration as the inputs, a prediction model for car body vibration acceleration was established based on several training algorithms and neural network structures. Then, the model was successfully applied to predict the car body vibration acceleration of test datasets on different segments of the same railway. The results show that the proposed method overcomes the complexity and uncertainty of the multiparameter coupling analysis in traditional theoretical models. The research findings boast a great potential for application.http://dx.doi.org/10.1155/2018/1752070 |
| spellingShingle | Shubin Zheng Qianwen Zhong Xiaodong Chai Xingjie Chen Lele Peng A Novel Prediction Model for Car Body Vibration Acceleration Based on Correlation Analysis and Neural Networks Journal of Advanced Transportation |
| title | A Novel Prediction Model for Car Body Vibration Acceleration Based on Correlation Analysis and Neural Networks |
| title_full | A Novel Prediction Model for Car Body Vibration Acceleration Based on Correlation Analysis and Neural Networks |
| title_fullStr | A Novel Prediction Model for Car Body Vibration Acceleration Based on Correlation Analysis and Neural Networks |
| title_full_unstemmed | A Novel Prediction Model for Car Body Vibration Acceleration Based on Correlation Analysis and Neural Networks |
| title_short | A Novel Prediction Model for Car Body Vibration Acceleration Based on Correlation Analysis and Neural Networks |
| title_sort | novel prediction model for car body vibration acceleration based on correlation analysis and neural networks |
| url | http://dx.doi.org/10.1155/2018/1752070 |
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