Performance analysis of linear and non-linear machine learning models for forecasting compressive strength of concrete-Reference-Cited by-同舟云学术

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Performance analysis of linear and non-linear machine learning models for forecasting compressive strength of concrete

Published:2024-06-21 Issue:1 Volume:11 Page:
ISSN:2331-1916
Container-title:Cogent Engineering
language:en
Short-container-title:Cogent Engineering

Author:

Mouli Kathi Chandra¹^ORCID,Raghavendran Ch. V.²,Mallikarjuna Rao Ch.¹^ORCID,Ushasree D.¹,Indupriya B.¹,Vatin Nikolai Ivanovich³⁴,Negi Anup Singh⁵

Affiliation:

1. Gokaraju Rangaraju Institute of Engineering & Technology, Hyderabad, India

2. Aditya College of Engineering & Technology, Surampalem, India

3. Russian Federation, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russia

4. Lovely Professional University, Phagwara, India

5. Uttaranchal University, Dehradun, India

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/23311916.2024.2368101

Reference31 articles.

1. Compressive strength prediction of Portland cement concrete with age using a new model

2. Neural networks for predicting compressive strength of structural light weight concrete

3. Prediction of compressive strength of concrete containing Pozzolanic materials by applying neural networks;Ayman A. H.;International Journal of Civil Engineering and Technology (IJCIET),2019

4. Quasi Analysis of Rainfall Prediction during Floods using Machine Learning

5. Evaluation of Random Forest and Adaboost tree-based ensemble classification and spectral band selection for ecotope mapping using airborne hyperspectral imagery

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