Research on HC-LSSVM Model for Soft Soil Settlement Prediction Based on Homotopy Continuation Method
Prediction of soft soil settlement is an important research topic in the field of civil engineering, and the least square support vector machine is one of the commonly used prediction methods at present. Nonetheless, the existing LSSVM models have problems of low search efficiency in the search proc...
| Main Authors: | , , , |
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| Format: | Article |
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MDPI AG
2021-11-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/22/10666 |
| _version_ | 1797511375926329344 |
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| author | Guangjun Cui Shenghua Xiong Cuiying Zhou Zhen Liu |
| author_facet | Guangjun Cui Shenghua Xiong Cuiying Zhou Zhen Liu |
| author_sort | Guangjun Cui |
| collection | DOAJ |
| description | Prediction of soft soil settlement is an important research topic in the field of civil engineering, and the least square support vector machine is one of the commonly used prediction methods at present. Nonetheless, the existing LSSVM models have problems of low search efficiency in the search process and lack of global optimal solution in the search results. In order to solve this problem, based on the leave-one-out cross-validation method, the homotopy continuation method was used to optimize the LSSVM model parameters, and then the HC-LSSVM model was constructed with the goal of minimizing the sum of squares of the prediction error of the full sample retention one. Finally, the rationality and correctness of the model are verified by engineering application. The results show that the HC-LSSVM model constructed in this study can accurately predict the settlement of soft ground, which is superior to the common LSSVM model and solves the problem that the parameters of LSSVM model cannot be solved optimally. The research results provide a new method for prediction of soft soil settlement. |
| first_indexed | 2024-03-10T05:44:24Z |
| format | Article |
| id | doaj.art-a7197a401dd84e06b75733f81ac1c7da |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T05:44:24Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-a7197a401dd84e06b75733f81ac1c7da2023-11-22T22:17:05ZengMDPI AGApplied Sciences2076-34172021-11-0111221066610.3390/app112210666Research on HC-LSSVM Model for Soft Soil Settlement Prediction Based on Homotopy Continuation MethodGuangjun Cui0Shenghua Xiong1Cuiying Zhou2Zhen Liu3School of Civil Engineering, Sun Yat-sen University, Zhuhai 519082, ChinaSchool of Civil Engineering, Sun Yat-sen University, Zhuhai 519082, ChinaSchool of Civil Engineering, Sun Yat-sen University, Zhuhai 519082, ChinaSchool of Civil Engineering, Sun Yat-sen University, Zhuhai 519082, ChinaPrediction of soft soil settlement is an important research topic in the field of civil engineering, and the least square support vector machine is one of the commonly used prediction methods at present. Nonetheless, the existing LSSVM models have problems of low search efficiency in the search process and lack of global optimal solution in the search results. In order to solve this problem, based on the leave-one-out cross-validation method, the homotopy continuation method was used to optimize the LSSVM model parameters, and then the HC-LSSVM model was constructed with the goal of minimizing the sum of squares of the prediction error of the full sample retention one. Finally, the rationality and correctness of the model are verified by engineering application. The results show that the HC-LSSVM model constructed in this study can accurately predict the settlement of soft ground, which is superior to the common LSSVM model and solves the problem that the parameters of LSSVM model cannot be solved optimally. The research results provide a new method for prediction of soft soil settlement.https://www.mdpi.com/2076-3417/11/22/10666soft soil settlement predictionLSSVM modelmodel parameter solutionhomotopy continuation methodHC-LSSVM model |
| spellingShingle | Guangjun Cui Shenghua Xiong Cuiying Zhou Zhen Liu Research on HC-LSSVM Model for Soft Soil Settlement Prediction Based on Homotopy Continuation Method Applied Sciences soft soil settlement prediction LSSVM model model parameter solution homotopy continuation method HC-LSSVM model |
| title | Research on HC-LSSVM Model for Soft Soil Settlement Prediction Based on Homotopy Continuation Method |
| title_full | Research on HC-LSSVM Model for Soft Soil Settlement Prediction Based on Homotopy Continuation Method |
| title_fullStr | Research on HC-LSSVM Model for Soft Soil Settlement Prediction Based on Homotopy Continuation Method |
| title_full_unstemmed | Research on HC-LSSVM Model for Soft Soil Settlement Prediction Based on Homotopy Continuation Method |
| title_short | Research on HC-LSSVM Model for Soft Soil Settlement Prediction Based on Homotopy Continuation Method |
| title_sort | research on hc lssvm model for soft soil settlement prediction based on homotopy continuation method |
| topic | soft soil settlement prediction LSSVM model model parameter solution homotopy continuation method HC-LSSVM model |
| url | https://www.mdpi.com/2076-3417/11/22/10666 |
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