Applications of machine learning in friction stir welding: Prediction of joint properties, real-time control and tool failure diagnosis
AH Elsheikh - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Abstract Machine learning (ML) methods have received immense attention as potential
models for modeling different manufacturing systems. This paper presents a comprehensive …
models for modeling different manufacturing systems. This paper presents a comprehensive …
Thermal, daylight, and energy potential of building-integrated photovoltaic (BIPV) systems: A comprehensive review of effects and developments
According to energy consumption data of the European Union, buildings account for 40% of
overall energy consumption in all sectors. The rise in building energy demand seriously …
overall energy consumption in all sectors. The rise in building energy demand seriously …
Predicting characteristics of dissimilar laser welded polymeric joints using a multi-layer perceptrons model coupled with archimedes optimizer
This study investigates the application of a coupled multi-layer perceptrons (MLP) model
with Archimedes optimizer (AO) to predict characteristics of dissimilar lap joints made of …
with Archimedes optimizer (AO) to predict characteristics of dissimilar lap joints made of …
A coupled artificial neural network with artificial rabbits optimizer for predicting water productivity of different designs of solar stills
In this study, a coupled multi-layer perceptrons (MLP) model with an artificial rabbits
optimizer (ARO) is developed to predict the water productivity of different designs of solar …
optimizer (ARO) is developed to predict the water productivity of different designs of solar …
[HTML][HTML] A new optimized artificial neural network model to predict thermal efficiency and water yield of tubular solar still
Tubular solar still is a simple light-weight desalination unit with a large condensing surface
compared with other types of solar stills. Regrettably, it suffers from the low water yield like …
compared with other types of solar stills. Regrettably, it suffers from the low water yield like …
[HTML][HTML] Kerf characteristics during CO2 laser cutting of polymeric materials: experimental investigation and machine learning-based prediction
This study uses advanced machine learning approaches to predict the kerf open deviation
(KOD) when a CO 2 laser is used to cut polymeric materials. Four polymeric materials …
(KOD) when a CO 2 laser is used to cut polymeric materials. Four polymeric materials …
Machine learning-based prediction and augmentation of dish solar distiller performance using an innovative convex stepped absorber and phase change material …
As well known, the solar distiller is one of the introduced solutions to the freshwater shortage
problem, but it is demerited by the low freshwater output. In this paper, a design modification …
problem, but it is demerited by the low freshwater output. In this paper, a design modification …
Modeling ultrasonic welding of polymers using an optimized artificial intelligence model using a gradient-based optimizer
In this study, a new hybrid artificial intelligence approach is proposed to model the ultrasonic
welding of a polymeric material blend. The proposed approach is composed of an ensemble …
welding of a polymeric material blend. The proposed approach is composed of an ensemble …
An optimized multilayer perceptrons model using grey wolf optimizer to predict mechanical and microstructural properties of friction stir processed aluminum alloy …
In the current investigation, AA2024 aluminum alloy is reinforced by alumina nanoparticles
using a friction stir process (FSP) with multiple passes. The mechanical properties and …
using a friction stir process (FSP) with multiple passes. The mechanical properties and …
[HTML][HTML] Random vector functional link network: recent developments, applications, and future directions
Neural networks have been successfully employed in various domains such as
classification, regression and clustering, etc. Generally, the back propagation (BP) based …
classification, regression and clustering, etc. Generally, the back propagation (BP) based …