A comparison of novel hybrid ensemble learners to predict the compressive strength of green engineering materials: a case of concrete composed of rice husk ash-Reference-Cited by-同舟云学术

A comparison of novel hybrid ensemble learners to predict the compressive strength of green engineering materials: a case of concrete composed of rice husk ash

Published:2024-04-08 Issue: Volume: Page:1-28
ISSN:1964-8189
Container-title:European Journal of Environmental and Civil Engineering
language:en
Short-container-title:European Journal of Environmental and Civil Engineering

Author:

Ghanizadeh Ali Reza¹,Tavana Amlashi Amir²,Dessouky Samer²,Ebrahimi Seyed Abolfazl³

Affiliation:

1. Department of Civil Engineering, Sirjan University of Technology, Sirjan, Iran;

2. School of Civil and Environmental Engineering and Construction Management, University of Texas at San Antonio, San Antonio, TX, USA

3. School of Natural Resources and Environment, University of Florida, Gainesville, FL, USA

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/19648189.2024.2335343

Reference146 articles.

1. Strength and Some Durability Properties of Concrete Containing Rice Husk Ash Produced in a Charcoal Incinerator at Low Specific Surface

2. The compatibility of bentonite/sepiolite plastic concrete cut-off wall material

3. Prediction of Geopolymer Concrete Compressive Strength Using Novel Machine Learning Algorithms

4. The properties of various igneous rocks for γ-ray shielding

5. Improving strength of concrete through partial usage of rice husk ash;AkshayTandon C.;International Research Journal of Engineering and Technology,2017

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