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...
Saved in:
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: | EN |
Published: |
MDPI AG
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/59ee155596294df6b4582f9338ca8190 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
THEORETICAL ANALYSIS OF INFLUENTIAL PARAMETERS TO COMPRESSION AND DECOMPRESSION PROCESS OF COMPRESSED OIL IN HYDRAULIC SYSTEMS OF THE PRESS
by: MILUTIN ŽIVKOVIĆ
Published: (2016) -
Presenting new models to determine subgrade reaction modulus (Ks) for optimizing foundation calculations in coarse grained soils
by: Salari,Pouya, et al.
Published: (2020) -
Some mechanical properties of plywood produced from eucalyptus, beech, and poplar veneer
by: Bal,Bekir Cihad, et al.
Published: (2014) -
Determining the peat soil dynamic properties using geophysical methods
by: Basri Kasbi, et al.
Published: (2021) -
Mathematical model for bulk modulus of hydraulic oil containing air bubbles
by: Sayako SAKAMA, et al.
Published: (2015)