Turkish Character Usage in Text Classification

Ali Aycan KOLUKISA

Abstract This study is prepared to examine the effects of Turkish character usage on text data by using multiple classifiers. Regression Classifiers, SVM, NB-Classifiers, and ANN are frequently used in supervised learning methods, especially in classification problems. Regression classifiers generally come in two types: as Linear and Logistic. There are also more than one type of Naive Bayes classifier. In our study, after mentioning the properties of Linear Regression and Logistic Regression classifiers in general terms, why Logistic Regression is much more suitable for this study is explaine ...Daha fazlası

Makale 2021 Journal of Artificial Intelligence and Data Science1 ( 1 ) , pp. 5 - 58 26 Görüntülenme

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Optimization of Process Parameters for Green Composites in Abrasive Water Jet Machining Process Using Neuro-Regression Analysis

LEVENT AYDIN

Kaynakça var.

Makale 2021 Journal of Artificial Intelligence and Data Science1 ( 1 ) , pp. 7 - 79 54 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 22 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 28 Görüntülenme

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Electron Beam Welding (EBW) of Aerospace Alloy (Inconel 825): Optimization and Modeling of Weld Bead Area

LEVENT AYDIN

This study investigates the optimum weld area on a popular aerospace alloy (i.e., Inconel 825) made by the electron beam welding technique. Welding speed (S), beam current (I), accelerating voltage (V), and beam oscillation (O) are considered as process parameters to study the weld bead area (WA) of the weldments. An instructive study on multiple non-linear neural regression analyses has been done as a basic introduction to neuro regression modeling with artificial neural network (ANN) philosophy. To do this, the experimental prediction has been modeled with 14 predictive functional structures ...Daha fazlası

Makale 2021 Journal of Artificial Intelligence and Data Science1 ( 1 ) , pp. 1 - 115 43 Görüntülenme