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Bulunan: 7 Adet 0.000 sn

Tür : Makale ✕Yayıncı : İzmir Katip Çelebi Ü ... ✕Dergi Adı : Journal of Artificia ... ✕Dergi Sayısı : 1 ✕Dergi Sayısı : 1 ✕Koleksiyon : YAPAY ZEKA VE VERİ B ... ✕Tam Metin : var ✕

Koleksiyon [2]

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Tam Metin [1]

Veritabanı [1]

Eser Sahibi [6]

Tür [1]

Yayın Tarihi [1]

Yayıncı [1]

Kayıt Giriş Tarihi [2]

Dergi Sayısı [1]

Yayın Dili [1]

Konu Başlıkları [20]

Dergi Adı [1]

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Erişime Açık

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

Erişime Açık

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 32 Görüntülenme

Erişime Açık

A Novel, Nelder-Mead Optimization Approach, based on Neuro-regression modeling for the Energy Efficiency Parameters of End Milling Process

ŞEYDA İŞBİLİR

Global crises are increasing day by day due to the rapid depletion of energy supplies around the planet. One of the goals of engineering is to prevent this situation by developing innovative solutions to this rapid energy consumption that has disappeared in the world. A solution could be to reduce the energy consumption of the machines that are used during production. In this study, a new design technique based on the neuro-regression approach and non-linear regression modeling was offered as an alternative to Taguchi design to reduce energy consumption. Thus, a cutting parameter optimization ...Daha fazlası

Makale 2021 Journal of Artificial Intelligence and Data Science1 ( 1 ) , pp. 9 - 105 29 Görüntülenme

Erişime Açık

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

Erişime Açık

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

Erişime Açık

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

Erişime Açık

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