Statistical analysis and Neural Network Modeling of functionally graded porous nanobeams vibration in an elastic medium by considering the surface effects

X Cheng, SH Al-Khafaji, M Hashemian… - … Applications of Artificial …, 2023 - Elsevier
The natural frequency of a clamped–clamped functionally graded porous (FGP) nanobeam
is predicted in this study. Material distribution is considered based on monotonous …

Sensitivity analysis of the artificial neural networks in a system for durability prediction of forging tools to forgings made of C45 steel

B Mrzygłód, M Hawryluk, M Janik… - The international journal …, 2020 - Springer
The article presents the results of a sensitivity analysis of artificial neural networks
developed for a system which predicts the durability of forging tools used in the selected hot …

[BOK][B] Data-driven evolutionary modeling in materials technology

N Chakraborti - 2022 - taylorfrancis.com
Due to efficacy and optimization potential of genetic and evolutionary algorithms, they are
used in learning and modeling especially with the advent of big data related problems. This …

Multi-objective optimization of buckling load and natural frequency in functionally graded porous nanobeams using non-dominated sorting genetic Algorithm-II

H Liu, A Basem, DJ Jasim, M Hashemian… - … Applications of Artificial …, 2025 - Elsevier
This study investigates the fundamental natural frequency and critical buckling load of
Functionally Graded Porous nanobeams supported by an elastic medium, addressing the …

Optimal process design in hot forging in terms of grain flow quality

MC Kim, SH Chung, MS Joun - International Journal of Automotive …, 2019 - Springer
With the improvement in the accuracy of simulation and computation time, the need for the
application of optimization technique in designing process parameters is increasing and is …

Determination of worst-case data using an adaptive surrogate model for real-time system

M Rashid, SAB Shah, M Arif, M Kashif - Journal of Circuits, Systems …, 2020 - World Scientific
The estimation of worst-case execution time (WCET) is a critical activity in the analysis of
real-time systems. Evolutionary algorithms are frequently employed for the determination of …

The effect of electrical discharge machining parameters on alloy DIN 1.2080 using the Taguchi method and determinant of optimal design of experiments

P Sadr, A Kolahdooz, SA Eftekhari - Journal of Naval Architecture and …, 2017 - banglajol.info
Abstract Electrical Discharge Machining (EDM) process is one of the most widely used
methods for machining. This method is used to form parts that conduct electricity. This …

[PDF][PDF] DRAFT COPY

M Rashid, SAB Shah, M Arif - researchgate.net
The estimation of worst-case execution time (WCET) is a critical activity in the analysis of
real-time systems. Evolutionary algorithms are frequently employed for the determination of …