Hybrid artificial intelligent for dielectric constant of concrete

Israa Adnan Najem; Kareem Fadhil Abood; Jaber Ghaib Talib

doi:10.30574/ijsra.2024.13.2.2356

ISSN Approved Journal || eISSN: 2582-8185 || CODEN: IJSRO2 || Impact Factor 8.2 || Google Scholar and CrossRef Indexed

Peer Reviewed and Referred Journal || Free Certificate of Publication

Research and review articles are invited for publication in March 2026 (Volume 18, Issue 3) Submit manuscript

Hybrid artificial intelligent for dielectric constant of concrete

Israa Adnan Najem ^{1, *}, Kareem Fadhil Abood ¹ and Jaber Ghaib Talib ²

1 Al-Furat AL-Awsat Technical University, Technical institute of Babylon.
2 AL-Mustaqbal University.

Research Article

International Journal of Science and Research Archive, 2024, 13(02), 3854-3858.
Article DOI: 10.30574/ijsra.2024.13.2.2356
DOI url: https://doi.org/10.30574/ijsra.2024.13.2.2356

Publication history

Received on 29 October 2024; revised on 14 December 2024; accepted on 16 December 2024

Abstract

Optimization of dielectric constant of concrete specifications based on hybrid artificial intelligent is used in this paper. in this study, neural network with feed forward neural network is applied in the system. The value of dielectric constant is estimated were determined by the number of hidden layers of NN.matlab is used with Simulink to enhance the complicated system.

Keywords

Dielectric constant; Neural network; Matlab; FFNN

Download Article PDF

https://ijsra.net/sites/default/files/fulltext_pdf/IJSRA-2024-2356.pdf

Preview Article PDF

How to cite this article

Israa Adnan Najem, Kareem Fadhil Abood and Jaber Ghaib Talib. Hybrid artificial intelligent for dielectric constant of concrete. International Journal of Science and Research Archive, 2024, 13(02), 3854-3858. https://doi.org/10.30574/ijsra.2024.13.2.2356

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.

All statements, opinions, and data contained in this publication are solely those of the individual author(s) and contributor(s). The journal, editors, reviewers, and publisher disclaim any responsibility or liability for the content, including accuracy, completeness, or any consequences arising from its use.