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Cement strength prediction using cloud-based machine learning techniques

Published:2020-09-17 Issue:4 Volume:5 Page:244-251
ISSN:2470-5314
Container-title:Journal of Structural Integrity and Maintenance
language:en
Short-container-title:Journal of Structural Integrity and Maintenance

Author:

Kumar Nand¹,Naranje Vishal²,Salunkhe Sachin³

Affiliation:

1. Department of Computer Science, Birla Institute of Technology and Science, Dubai, UAE

2. Department of Mechanical Engineering, Amity University, Dubai, UAE

3. Department of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, India

Publisher

Informa UK Limited

Subject

Mechanical Engineering,General Materials Science,Building and Construction,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/24705314.2020.1783122

Reference26 articles.

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

2. Prediction of the compressive strength of normal and high-performance concretes using M5P model tree algorithm

3. Neural networks analysis of compressive strength of lightweight concrete after high temperatures

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1. An evolutionary functional link artificial neural network for assessment of compressive strength of concrete structures;Ain Shams Engineering Journal;2024-03

2. Machine learning-based prediction of compressive strength for limestone calcined clay cements;Journal of Building Engineering;2023-10

3. Kiln predictive modelization for performance optimization;The International Journal of Advanced Manufacturing Technology;2023-05-26

4. Water absorption prediction of nanopolymer hydrophobized concrete surface using texture analysis and machine learning algorithms;Construction and Building Materials;2023-04

5. Kiln Predictive Modelisation for Performance Optimization;2023-01-16

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