An Intelligent Prediction Method of the Karst Curtain Grouting Volume Based on Support Vector Machine. (7th November 2020)
- Record Type:
- Journal Article
- Title:
- An Intelligent Prediction Method of the Karst Curtain Grouting Volume Based on Support Vector Machine. (7th November 2020)
- Main Title:
- An Intelligent Prediction Method of the Karst Curtain Grouting Volume Based on Support Vector Machine
- Authors:
- Niu, Jiandong
Wang, Bin
Wang, Haifa
Deng, Zhiwei
Liu, Jianxin
Li, Zewei
Chen, Guanjun
Zhang, Botao - Other Names:
- Zhao Yanlin Academic Editor.
- Abstract:
- Abstract : The prediction of the grouting volume is a very important task in the grouting quality control. Because of the concealment and complexity of the karst curtain grouting engineering, there is little research on the prediction of the karst curtain grouting volume (KCGV), and the prediction is hindered by the practical problems of small samples, high dimensions, and nonlinearity. In the study, based on the basic idea of support vector machine (SVM), a multiparameter comprehensive intelligent prediction method of the KCGV is proposed, which overcomes the limitation of few sample data in practical engineering. This method takes the grouting construction conditions and the slurry conditions which control the slurry diffusion as the input parameters, which are the basic data which can be easily obtained in the field grouting process. This feature greatly improves the prediction accuracy and generalization performance of the method. The intelligent prediction method of the KCGV based on SVM is applied to a typical karst curtain grouting project. The mean absolute error of the prediction results is 3.47 L/m, and the mean absolute percentage error of the prediction results is 5.97%. The results show that the proposed prediction method has an excellent prediction effect on the KCGV and can provide practical and beneficial help for the field karst curtain grouting project.
- Is Part Of:
- Geofluids. Volume 2020(2020)
- Journal:
- Geofluids
- Issue:
- Volume 2020(2020)
- Issue Display:
- Volume 2020, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 2020
- Issue:
- 2020
- Issue Sort Value:
- 2020-2020-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-11-07
- Subjects:
- Hydrogeology -- Periodicals
Sedimentary basins -- Periodicals
Fluids -- Migration -- Periodicals
Groundwater flow -- Periodicals
Geothermal resources -- Periodicals
Fluid dynamics -- Periodicals
Earth -- Crust -- Periodicals
551.49 - Journal URLs:
- https://onlinelibrary.wiley.com/journal/14688123 ↗
https://www.hindawi.com/journals/geofluids/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1155/2020/8892106 ↗
- Languages:
- English
- ISSNs:
- 1468-8115
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4121.445000
British Library STI - ELD Digital store - Ingest File:
- 14984.xml