Version 1
: Received: 20 September 2024 / Approved: 23 September 2024 / Online: 24 September 2024 (08:32:26 CEST)
How to cite:
ALTUNCI, Y. T. A Comprehensive Study on the Prediction of Concrete Compressive Strength. Preprints2024, 2024091766. https://doi.org/10.20944/preprints202409.1766.v1
ALTUNCI, Y. T. A Comprehensive Study on the Prediction of Concrete Compressive Strength. Preprints 2024, 2024091766. https://doi.org/10.20944/preprints202409.1766.v1
ALTUNCI, Y. T. A Comprehensive Study on the Prediction of Concrete Compressive Strength. Preprints2024, 2024091766. https://doi.org/10.20944/preprints202409.1766.v1
APA Style
ALTUNCI, Y. T. (2024). A Comprehensive Study on the Prediction of Concrete Compressive Strength. Preprints. https://doi.org/10.20944/preprints202409.1766.v1
Chicago/Turabian Style
ALTUNCI, Y. T. 2024 "A Comprehensive Study on the Prediction of Concrete Compressive Strength" Preprints. https://doi.org/10.20944/preprints202409.1766.v1
Abstract
There is an extensive body of research in the literature focusing on predicting the mechanical properties of concrete, such as compressive strength. Summarizing the current studies following the valuable contributions of researchers will serve as a guide for future studies and researchers. To this end, this study aims to identify the key authors, sources, institutions, and countries that have contributed to the prediction of concrete compressive strength. Additionally, it aims to provide researchers with comprehensive information on prominent research themes, trends, and gaps in the literature related to the prediction of concrete compressive strength. For this purpose, 2319 articles on the prediction of concrete compressive strength published from 2000 to 19th August 2024 were identified through the Scopus Database. The scientific measurement analyses were conducted using VOSviewer software. Upon reviewing the relevant research, it was found that machine learning methods are frequently used in predicting concrete compressive strength. In this context, the study will make significant contributions to the literature by examining leading institutions, countries, authors, and sources in the field, synthesizing data, and highlighting research areas, gaps, and trends related to concrete compressive strength prediction.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
