Machine Learning Methods to Predict and Analyse Unconfined Compressive Strength of Stabilised Soft Soil with Polypropylene Columns-Reference-Cited by-同舟云学术

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Machine Learning Methods to Predict and Analyse Unconfined Compressive Strength of Stabilised Soft Soil with Polypropylene Columns

Published:2023-06-14 Issue:1 Volume:10 Page:
ISSN:2331-1916
Container-title:Cogent Engineering
language:en
Short-container-title:Cogent Engineering

Author:

Hoque Md. Ikramul¹,Hasan Muzamir¹,Islam Md Shofiqul²,Houda Moustafa³,Abdallah Mirvat³,Sobuz Md. Habibur Rahman⁴

Affiliation:

1. Faculty of Civil Engineering Technology, Universiti Malaysia Pahang, Gambang, Malaysia

2. Faculty of Computing, Universiti Malaysia Pahang, Gambang, Malaysia

3. College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait

4. Department of Building Engineering and Construction Management, Khulna University of Engineering & Technology, Khulna, Bangladesh

Publisher

Informa UK Limited

Subject

General Engineering,General Chemical Engineering,General Computer Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/23311916.2023.2220492

Reference36 articles.

1. A non-parametric mixture of Gaussian naive Bayes classifiers based on local independent features

2. Review the performance of the Bernoulli Naïve Bayes Classifier in Intrusion Detection Systems using Recursive Feature Elimination with Cross-validated selection of the best number of features

3. Experimental Study on Shear Strength of Cohesive Soils Reinforced with Stone Columns

4. Enhanced and Effective Computerized Multi Layered Perceptron based Back Propagation Brain Tumor Detection with Gaussian Filtering

5. The settlement performance of stone column foundations

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1. Novel prediction of unconfined compressive strength with least square support vector regression coupled with meta-heuristic optimizers;Multiscale and Multidisciplinary Modeling, Experiments and Design;2024-08-02

2. The unconfined compressive strength estimation of rocks using a novel hybridization technique based on the regulated Gaussian processor;Journal of Engineering and Applied Science;2024-04-29

3. Prediction of Unconfined Compressive Strength of Stabilized Sand Using Machine Learning Methods;Indian Geotechnical Journal;2024-04-07

4. Enhancing unconfined compressive strength of stabilized soil with lime and cement prediction through a robust hybrid machine learning approach utilizing Naive Bayes Algorithm;Journal of Engineering and Applied Science;2024-04-01

5. Assessment of Unconfined Compressive Strength of Stabilized Soil Using Artificial Intelligence Tools: A Scientometrics Review;Studies in Systems, Decision and Control;2024

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