Abstract
The swelling potentiality is a vital property of fine-grained soils strictly related to the index properties and chemical composition. The integration of machine learning techniques and geotechnical parameters provided a new integrative approach for predicting the free swelling index (FSI) and the swelling pressure (SP). In this paper, an adaptive neuro-fuzzy inference system (ANFIS) using named Reptile Search Algorithm (RSA) is presented to predict the swelling potentiality for fine-grained soils in the foundation bed at El Sherouk city, Egypt. The developed predictive model, named RSA-ANFIS, used as input measured 108 natural fine-grained soil samples of index geotechnical parameters and chemical composition as input data and the measured data of the free swelling index and the swelling pressure as output data. To justify the performance of the developed model, a comparative study was carried out, and the results show that the developed RSA-ANFIS has a high performance over the competitive methods in terms of coefficient of determination, root mean square error (RMSE), and mean absolute error (MAE). This new integrative approach is considered at the highly developed stage to predict and improve the analysis of multi-parameter soil behavior and could be applied in other objective variable datasets.
Highlights
Swelling soils are considered as the more common problematic soils worldwide, and the investigation of these soils has a high priority challenge. These soils are composed of fine-grained soils. These soils are essential in different geotechnical practices
The has a high priority challenge. These soils are considered as problematic soils, has a high priority challenge
These soils are considered as problematic soils, and and characterization their characterization is essential anywhere in different geotechnical engineering their is essential anywhere in different geotechnical engineering practices
Summary
Swelling soils are considered as the more common problematic soils worldwide, and the investigation of these soils has a high priority challenge. These soils are composed of fine-grained soils. The mineralogical and chemical composition effect are not clarified and explicated on the index geotechnical properties of the clayey soils with the new and effective methods [1,3,4]. The effects of mineralogical and chemical composition are not clarified and explicated on index geotechnical properties of the clayey soils with the new and effective methods [5,6,7]
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