The artificial neural network (ANN) approach motivated by the biological nervous system is
an inspiring mathematical tool that simulates many complicated engineering applications …

Synthetic fibers were replaced with natural fibers in the composite world because natural
fibers are greater motivational to researchers concerning environmental problems …

The composite laminates with circular holes find numerous applications in aerospace,
automobile manufacturing and other fields due to the design and assembly of structural …

This study intends to predict the tensile strength of polymer concrete (PC) composites using
one of the deep learning-based methods called deep neural network (DNN). A database …

The physical, mechanical, and thermal characteristics of loofa fiber-alumina (Al 2 O 3) and
loofa fiber-aluminum silicon carbide (Al-SiC) reinforced with epoxy, vinyl-ester, and …

Using artificial intelligence‐based methods in predicting material properties, in addition to
high accuracy, saves time and money. This paper models and predicts the fracture …

The current study is an attempt to investigate the usefulness of a deep learning-based
method, backpropagation deep neural network (DNN) for the prediction of the mechanical …

This review aims to provide a detailed analysis of the synthesis methods, properties, and
applications of natural fiber‐reinforced epoxy composites, highlighting their potential as …

In this paper, the geometry factors of mode I and mode II (YI and YII) and the normalized T‐
stress (T*) of the centrally cracked Brazilian disk specimen are predicted using a deep …

Natural fibre composites are ideal material substitutes for combating the issues of pollution
and non-biodegradability. Several industries, the automobile industry, in particular, have …