Modeling and Design Optimization to Determine the Mechanical Properties of a Recent Composite

Naciye Burcu KARTAL

This study proposes an appropriate optimization model for determining a new composite material's mechanical properties by neuro-regression analysis. This new composite material is obtained by combining hemp and polypropylene fibers. It was developed for the sector of upholstered furniture. First, different multiple regression models have been tried for input and output values. The R2 training, R2 testing, R2 validation, and minimum, maximum values were determined for each model. Then, the stochastic optimization approach is used to predict and optimize the mechanical properties of the new bioc ...Daha fazlası

Makale 2021 Journal of Artificial Intelligence and Data Science1 ( 1 ) , pp. 8 - 88 29 Görüntülenme

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1st International Congress on Artificial Intelligence and Data Science (İzmir : 2021)

İzmir Kâtip Çelebi Üniversitesi

Çevrimiçi (362 sayfa : şekil, tablo ; 26 cm.).

Kitap 2021 İzmir Kâtip Çelebi Üniversitesi 28 Görüntülenme

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Estimation of Scattering Parameters of U-Slotted Rectangular RFID Patch Antenna with Machine Learning Models

İsmail AKDAĞ

Abstract In this study, machine learning-based models have been used to estimate the return loss parameters of the operational resonant frequency of the U-slotted UHF RFID antenna. The data set utilized, consisting of 544 instances, has been collected from the simulation software as a consequence of the parametric evaluation of the antenna design parameters. Distinct machine learning methods have been used on two different types of output data, complex and linear scattering parameters, and the models' prediction performance has been evaluated. In the single-output regression models, a mean-squ ...Daha fazlası

Makale 2021 Journal of Artificial Intelligence and Data Science1 ( 1 ) , pp. 6 - 70 19 Görüntülenme

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Modeling and optimum design for wire electrical discharge machining of γ titanium aluminide alloy

ÖMER FARUK BÜYÜKYAVUZ

Wire electrical discharge machining (WEDM) of γ titanium aluminide is the subject of the current research. Due to the large number of process variables and sophisticated stochastic process mechanisms, selecting the best machining parameter combinations for increased cutting efficiency and accuracy is a difficult task in WEDM. In general, there is no perfect combination that can produce the fastest cutting speed and the finest surface finish quality at the same time. For this purpose, the data were selected from a literature study. This study describes an attempt to devise a suitable machining ...Daha fazlası

Makale 2021 Journal of Artificial Intelligence and Data Science1 ( 1 ) , pp. 8 - 95 21 Görüntülenme