دورية أكاديمية

Improving the Mechanical Performance of Biocomposite Plaster/ Washingtonia filifera: Optimization Comparison Between ANN and RSM Approaches

التفاصيل البيبلوغرافية
العنوان: Improving the Mechanical Performance of Biocomposite Plaster/ Washingtonia filifera: Optimization Comparison Between ANN and RSM Approaches
المؤلفون: Ahmed Belaadi, Messaouda Boumaaza, Hassan Alshahrani, Mostefa Bourchak, Hamid Satha
المصدر: Journal of Natural Fibers, Vol 20, Iss 1 (2023)
بيانات النشر: Taylor & Francis Group, 2023.
سنة النشر: 2023
المجموعة: LCC:Science
LCC:Textile bleaching, dyeing, printing, etc.
مصطلحات موضوعية: washingtonia filifera, plaster-gypsum, tg/dsc, prediction, artificial neural networks, response surface methodology, Science, Textile bleaching, dyeing, printing, etc., TP890-933
الوصف: The present research is an extension of a previous paper published by the authors. In the first part of the research, the flexural properties of Washingtonia filifera (WF) fiber-reinforced plaster composite treated with sodium bicarbonate were explored using response surface method statistics. In the current study, the data was analyzed using artificial neural network tool. The main objective of the current research is to model the flexural properties of an environmentally friendly gypsum biocomposite reinforced with treated and untreated WF fibers using response surface method and artificial neural networks. For this purpose, the study reports a comparative approach between models predicted by response surface methodology (RSM) and artificial neural networks (ANNs). The statistical results as root mean square error and coefficient of determination reveal that ANN and RSM are effective techniques for bending properties prediction of plaster/WF biocomposites. In addition, ANN and RSM models correlate highly with the experimental data. However, artificial neural network model displayed more accuracy.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1544-0478
1544-046X
15440478
Relation: https://doaj.org/toc/1544-0478; https://doaj.org/toc/1544-046X
DOI: 10.1080/15440478.2023.2170945
URL الوصول: https://doaj.org/article/23bc09ac88a749f1803821c6a5118f7e
رقم الأكسشن: edsdoj.23bc09ac88a749f1803821c6a5118f7e
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:15440478
1544046X
DOI:10.1080/15440478.2023.2170945