Predicting mechanical properties of self-healing concrete with Trichoderma Reesei Fungus using machine learning-Reference-Cited by-同舟云学术

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Predicting mechanical properties of self-healing concrete with Trichoderma Reesei Fungus using machine learning

Published:2024-01-27 Issue:1 Volume:11 Page:
ISSN:2331-1916
Container-title:Cogent Engineering
language:en
Short-container-title:Cogent Engineering

Author:

Chiadighikaobi Paschal Chimeremeze¹^ORCID,Hematibahar Mohammad²,Kharun Makhmud²,Stashevskaya Nadezhda A.²,Camara Kebba³

Affiliation:

1. Department of Civil Engineering, Afe Babalola University, Ado-Ekiti, Nigeria

2. Reinforced Concrete and Stone Structures, Moscow State University of Civil Engineering, Moscow, Russia

3. Estate & Civil Engineering Department, Gambia port Authority, Banjul, The Gambia

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/23311916.2024.2307193

Reference42 articles.

1. Sustainable design guidelines for additive manufacturing applications

2. Performance Comparison of SVM and ANN in Predicting Compressive Strength of Concrete

3. Geomorphological, Geological and Engineering Geological Aspects for Sustainable Urban Planning of Mymensingh City, Bangladesh

4. The development of a radial based integrated network for the modelling of 3D fused deposition

5. Common features and interesting differences in transcriptional responses to secretion stress in the fungi Trichoderma reesei and Saccharomyces cerevisiae

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Advances in microbial self-healing concrete: A critical review of mechanisms, developments, and future directions;Science of The Total Environment;2024-10

2. Analysis of the Current State of Research on Bio-Healing Concrete (Bioconcrete);Materials;2024-09-13

3. Analysis of Models to Predict Mechanical Properties of High-Performance and Ultra-High-Performance Concrete Using Machine Learning;Journal of Composites Science;2024-07-26

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