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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

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Assessment of Fouling in Plate Heat Exchangers with Machine Learning Algorithms

Ceren VATANSEVER

Fouling is the accumulation of undesired particles on heat transfer surfaces which affects the heat transfer performance of a heat exchanger negatively. The accumulation of these particles prevents heat from being transformed through the heat exchangers by generating a fouling layer-like insulation. The main aim of the thesis is to investigate the machine learning algorithms to classify and predict the fouling status of PHE used in combi-boilers, to generate the background of the predictive maintenance, besides investigating the fouling effect on PHEs in terms of heat transfer and energy consu ...Daha fazlası

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Fabric Defect Classification Using Combination of Deep Learning and Machine Learning

Fatma Günseli YAŞAR ÇIKLAÇANDIR

Automatic systems can be used in many areas, such as the production stage in factories, country defense, and traffic control. They provide the opportunity to reach results faster with higher success rates thanks to human-computer vision cooperation. In this study, it is aimed to develop an intelligent system that automatically detects and classifies defects in fabrics. Thanks to the developed system, the cause of the malfunction is eliminated, and the recurrence of the malfunction is prevented. Using deep learning methods in fabric defect classification studies has a disadvantage compared to o ...Daha fazlası

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