Abstract
In order to effectively predict the settlement of soft soil foundation, improve the accuracy of road soft soil foundation settlement prediction, and improve the safety of the project, this paper proposes an optimized SVM-AR model and discusses the application scope of the SVM model and the time series AR model, respectively. The SVM-AR model is proposed by combining the respective advantages of the two types of models. Firstly, the prediction method of foundation settlement is analyzed and studied, and then the improved ABC algorithm is used to optimize the SVM model. Secondly, the optimized SVM model is combined with the AR model, the ABC-SVM model is used to predict the trend settlement, and the AR model is used to predict the random settlement and then combined to obtain the predicted settlement. The example verification shows that SVM-AR is more accurate than the SVM model prediction results and better reflects the settlement process of highway soft soil foundation.
Highlights
With the rapid development of my country’s economy, a large number of rural population poured into cities, resulting in an increasing shortage of urban land
The construction of some airports, granaries, oil storage tanks, and large steel plants has shifted to soft soil areas with special geological environments. e most important thing to build structures in these soft soil areas is to solve the problems of foundation settlement and stability of structures
E most important mechanical properties of the soil after repeated loads are the strength of the soil and the deformation of the soil. e influence of the settlement of the foundation on the upper buildings can be accurately determined according to the deformation of the soil under the action of long-term cyclic loads
Summary
With the rapid development of my country’s economy, a large number of rural population poured into cities, resulting in an increasing shortage of urban land. E most important thing to build structures in these soft soil areas is to solve the problems of foundation settlement and stability of structures. E influence of the settlement of the foundation on the upper buildings can be accurately determined according to the deformation of the soil under the action of long-term cyclic loads. It is one of the main research topics in the field of civil engineering [7]. Erefore, accurately predicting the settlement of highway soft soil foundation is an important geotechnical problem. With the continuous investment in highway construction and the increase in the calculation section of soft soil subgrade, a model is needed that can and accurately predict settlement. Erefore, this paper proposes an optimized SVM-AR combination model, uses the improved ABC algorithm to optimize the SVM, and uses the improved SVM model and AR model to predict the trend and random quantities of building settlement deformation to reflect the foundation settlement. e characteristics of regularity and randomness make the prediction results more accurate
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