On Random Subspace Optimization-Based Hybrid Computing Models Predicting the California Bearing Ratio of Soils

On Random Subspace Optimization-Based Hybrid Computing Models Predicting the California Bearing Ratio of Soils

The California Bearing Ratio (CBR) is an important index for evaluating the bearing capacity of pavement subgrade materials. In this research, random subspace optimization-based hybrid computing models were trained and developed for the prediction of the CBR of soil. Three models were developed, nam...

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Bibliographic Details
Main Authors: Duong Kien Trong, Binh Thai Pham, Fazal E. Jalal, Mudassir Iqbal, Panayiotis C. Roussis, Anna Mamou, Maria Ferentinou, Dung Quang Vu, Nguyen Duc Dam, Quoc Anh Tran, Panagiotis G. Asteris
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Materials
Subjects:
California Bearing Ratio
modulus of subgrade reaction
elastic modulus
metaheuristic algorithms
Online Access:https://www.mdpi.com/1996-1944/14/21/6516

Internet

https://www.mdpi.com/1996-1944/14/21/6516

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