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...

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Autores principales:	Guangjun Cui, Shenghua Xiong, Cuiying Zhou, Zhen Liu
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	soft soil settlement prediction LSSVM model model parameter solution homotopy continuation method HC-LSSVM model Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/a7197a401dd84e06b75733f81ac1c7da
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spelling	oai:doaj.org-article:a7197a401dd84e06b75733f81ac1c7da2021-11-25T16:34:39ZResearch on HC-LSSVM Model for Soft Soil Settlement Prediction Based on Homotopy Continuation Method10.3390/app1122106662076-3417https://doaj.org/article/a7197a401dd84e06b75733f81ac1c7da2021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/22/10666https://doaj.org/toc/2076-3417Prediction 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.Guangjun CuiShenghua XiongCuiying ZhouZhen LiuMDPI AGarticlesoft soil settlement predictionLSSVM modelmodel parameter solutionhomotopy continuation methodHC-LSSVM modelTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10666, p 10666 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	soft soil settlement prediction LSSVM model model parameter solution homotopy continuation method HC-LSSVM model Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	soft soil settlement prediction LSSVM model model parameter solution homotopy continuation method HC-LSSVM model Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Guangjun Cui Shenghua Xiong Cuiying Zhou Zhen Liu Research on HC-LSSVM Model for Soft Soil Settlement Prediction Based on Homotopy Continuation Method
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.
format	article
author	Guangjun Cui Shenghua Xiong Cuiying Zhou Zhen Liu
author_facet	Guangjun Cui Shenghua Xiong Cuiying Zhou Zhen Liu
author_sort	Guangjun Cui
title	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_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_sort	research on hc-lssvm model for soft soil settlement prediction based on homotopy continuation method
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/a7197a401dd84e06b75733f81ac1c7da
work_keys_str_mv	AT guangjuncui researchonhclssvmmodelforsoftsoilsettlementpredictionbasedonhomotopycontinuationmethod AT shenghuaxiong researchonhclssvmmodelforsoftsoilsettlementpredictionbasedonhomotopycontinuationmethod AT cuiyingzhou researchonhclssvmmodelforsoftsoilsettlementpredictionbasedonhomotopycontinuationmethod AT zhenliu researchonhclssvmmodelforsoftsoilsettlementpredictionbasedonhomotopycontinuationmethod
_version_	1718413094931136512

Research on HC-LSSVM Model for Soft Soil Settlement Prediction Based on Homotopy Continuation Method

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