Groutability prediction of microfine cement based soil improvement using evolutionary LS-SVM inference model

Abstract

Permeation grouting is a widely used technique for soil improvement in construction engineering. Thus, predicting the results of the grouting activity is a particularly interesting topic that has drawn the attention of researchers both from the academic field and industry. Recent literature has indicated that artificial intelligence (AI) approaches for groutability prediction are capable of delivering better performance than traditional formula-based ones. In this study, a novel AI method, evolutionary Least Squares Support Vector Machine Inference Model for groutability prediction (ELSIM-GP), is proposed to forecast the result of grouting activity that utilizes microfine cement grout. In the model, Least Squares Support Vector Machine (LS-SVM) is a supervised machine learning technique that is employed to learn the decision boundary for classifying high dimensional data. Differential Evolution (DE) is integrated into ELSIM-GP for automatically optimizing its tuning parameters. 240 historical cases of grouting process for sandy silt soil have been collected to train, validate, and test the inference model. Experimental results demonstrated that ELSIM-GP can overcome other benchmark approaches in terms of forecasting accuracy. Therefore, the proposed approach is a promising alternative for predicting groutability.

Keywords:

• groutability prediction
• Least Squares Support Vector Machine
• Differential Evolution
• machine learning
• artificial intelligence

Additional information

Notes on contributors

Min-Yuan Cheng

Min-Yuan CHENG. He is currently a Professor at the Department of Civil and Construction Engineering, National Taiwan University of Science and Technology. He holds lectures in Construction Automation and Construction Process Reengineering. He has published many papers in various international journals such as Journal of Civil Engineering and Management, Automation in Construction, Journal of Construction Engineering and Management, and Expert Systems with Applications. His research interests include management information system, applications of artificial intelligence, and construction management process reengineering.

Nhat-Duc Hoang

Nhat-Duc HOANG. He is currently a researcher and lecturer at Center of Research and Development, Duy Tan University. He got the MSc. and PhD. degrees at National Taiwan University of Science and Technology. He has published papers in various international journals such as Journal of Civil Engineering and Management, Automation in Construction, and Journal of Computing in Civil Engineering. His research focuses on applications of Artificial Intelligence in construction engineering and management.