Optimization of electric vehicle design problems using improved electric eel foraging optimization algorithm
This paper introduces a novel approach, the Modified Electric Eel Foraging Optimization
(EELFO) algorithm, which integrates artificial neural networks (ANNs) with metaheuristic …
(EELFO) algorithm, which integrates artificial neural networks (ANNs) with metaheuristic …
Artificial neural network infused quasi oppositional learning partial reinforcement algorithm for structural design optimization of vehicle suspension components
This paper introduces and investigates an enhanced Partial Reinforcement Optimization
Algorithm (E-PROA), a novel evolutionary algorithm inspired by partial reinforcement theory …
Algorithm (E-PROA), a novel evolutionary algorithm inspired by partial reinforcement theory …
A new modified version of mountain gazelle optimization for parameter extraction of photovoltaic models
This study addresses the challenges in accurately estimating photovoltaic (PV) parameters
for solar energy applications by enhancing parameter extraction processes to improve the …
for solar energy applications by enhancing parameter extraction processes to improve the …
Experimental and numerical investigation of crash performances of additively manufactured novel multi-cell crash box made with CF15PET, PLA, and ABS
In this study, a novel multi-cell crash box was designed and produced using 15% short
carbon fiber reinforced polyethylene terephthalate (CF15PET), polylactic acid (PLA), and …
carbon fiber reinforced polyethylene terephthalate (CF15PET), polylactic acid (PLA), and …
Optimization of vehicle conceptual design problems using an enhanced hunger games search algorithm
Electric vehicles have become a standard means of transportation in the last 10 years. This
paper aims to formalize design optimization problems for electric vehicle components. It …
paper aims to formalize design optimization problems for electric vehicle components. It …
Optimization of vehicle crashworthiness problems using recent twelve metaheuristic algorithms
In recent years, numerous optimizers have emerged and been applied to address
engineering design challenges. However, assessing their performance becomes …
engineering design challenges. However, assessing their performance becomes …
Mechanical behavior of composite pipe structures under compressive force and its prediction using different machine learning algorithms
I Bozkurt - Materials Testing, 2025 - degruyter.com
Thanks to machine learning algorithms, the performance of composites with high energy
absorption capacity can be predicted with high accuracy rates with a small number of data …
absorption capacity can be predicted with high accuracy rates with a small number of data …
Evolutionary optimization technique to minimize energy consumption for dry turning operation processes
Considering the extensive applications of turning and facing operations in mechanical
engineering manufacturing, the energy consumption of machining equipment has emerged …
engineering manufacturing, the energy consumption of machining equipment has emerged …
[HTML][HTML] Short-term wind power prediction based on IBOA-AdaBoost-RVM
Y Yuan, Q Yang, J Ren, K Li, Z Wang, Y Li… - Journal of King Saud …, 2024 - Elsevier
This study introduces an innovative model, namely IBOA-AdaBoost-RVM, which leverages
the Improved Butterfly Optimization Algorithm (IBOA), Adaptive Boosting (AdaBoost), and …
the Improved Butterfly Optimization Algorithm (IBOA), Adaptive Boosting (AdaBoost), and …
Prediction of rolling force during isothermal rolling process based on machine learning
W Lian, F Du, Q Pei - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
The Artificial neural networks (ANN) model established in this study can accurately predict
the rolling force of Titanium-Aluminium (TiAl) alloy during isothermal rolling process, and …
the rolling force of Titanium-Aluminium (TiAl) alloy during isothermal rolling process, and …