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Artículos de revistas sobre el tema "Yapay Sini Ağları"

Autor: Grafiati

Publicado: 7 de junio de 2025

Última modificación: 2 de agosto de 2025

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1

Çelik, Serpil, Haluk Bengü, and Hüseyin Nazmi Kartal Demirgüneş. "BIST-Teknoloji Endeksinde İşlem Gören Firmaların Nakit Akışlarının Yapay Sinir Ağları ile Tahminlenmesi." Muhasebe ve Vergi Uygulamaları Dergisi 18, no. 2 (2025): 381–98. https://doi.org/10.29067/muvu.1639976.

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Firmaların günlük faaliyetlerini sürdürebilmesi, yatırım fırsatlarını değerlendirebilmesi ve finansman sağlama imkanlarını artırabilmesi, likidite yeterliliğinin sağlanması ile yakından ilişkilidir. Yatırımcılar ve hissedarlar gibi paydaşlar, firmanın mali durumunu değerlendirirken likidite düzeyine de odaklanmaktadır. Bu nedenle, nakit akışlarının etkili bir şekilde yönetilebilmesi için gelecekteki nakit akışlarının doğru bir şekilde tahmin edilmesi büyük önem taşımaktadır. Bu çalışmanın amacı, 2016-2021 döneminde hisse senetleri BIST Teknoloji Endeksi’nde işlem gören 19 adet firmanın nakit a

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2

Uğur Balcı, Aysu. "Dijital Sine-Forum: Kuru Otlar Üstüne Filminin Seyirci/Kullanıcı Yorumları Üzerine Bir Değerlendirme." Yeni Medya Dergisi, no. 18 (June 30, 2025): 291–305. https://doi.org/10.55609/yenimedya.1614423.

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Film izleme pratiklerinin yanı sıra seyir sonrasında filmi tartışmak ve yorumda bulunmak dijital kültürün parçası haline gelmektedir. Hem dijital platformlardan film izlemek hem de dijital alanda içerikle ilgili fikirlerin paylaşılması, günümüzde seyircinin, kullanıcı olduğu bir düzlemde ele alınması gerekliliğini ortaya çıkarmaktadır. Bu bağlamda dijitalleşmenin imkanları sine-foruma olanak vermektedir. Sine-forum, film üzerine düşünen seyircileri buluşturan ortak ağlardır. Katılımcı kültürün bir unsuru olan ağlar, birbirini tanımayan seyircileri ortak mecrada buluşturmaktadır. Çalışmanın ama

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3

BAŞPINAR TUNCAY, Ebru, Ekin KÖKEN, and Şemsettin KILINÇARSLAN. "ESTIMATION OF CONCRETE STRENGTH PROPERTIES THROUGH THE RESPONSE SURFACE METHODOLOGY, GENETIC ALGORITHM, AND ARTIFICIAL NEURAL NETWORKS." Mühendislik Bilimleri ve Tasarım Dergisi 10, no. 2 (2022): 429–41. http://dx.doi.org/10.21923/jesd.1013463.

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Bu çalışmada, beton dayanım özellikleri yüzey tepki yöntemi, genetik algoritma ve yapay sinir ağları yöntemleri ile analiz edilmiştir. Altı farklı beton agregası kullanılarak küp (10x10x10 cm) ve prizmatik (15x15x60 cm) beton numuneleri hazırlanmış olup, beton tek eksenli basınç dayanımı (UCSc) ve eğilme dayanımının (FSc) tahminlenmesi için bazı tahmin modeller geliştirilmiştir. Geliştirilen modellerde beton yoğunluğu (ρc), beton agregalarının Los Angeles aşınma kaybı (LAA) ve betonlara ait P dalgası hızı (Vpc) gibi parametreler kullanılmıştır. Elde edilen modellerin performansları bazı istati

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4

KARAPINAR, DENIZ. "Meme Kanseri Teşhisi Üzerine Yapılan İstatistiksel Analiz ve Makine Öğrenmesi Uygulamaları." Turkish Journal of Statistics and Data Science 01, no. 1 (2025): 41–53. https://doi.org/10.5281/zenodo.15364696.

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5

SARI, Salim Sercan. "Predicting Financial Stress Index Using Wavelet Transform Artificial Neural Networks." Journal of International Scientific Researches 7, no. 3 (2022): 282–96. http://dx.doi.org/10.23834/isrjournal.1159770.

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Finansal risk ve belirsizlikler nedeniyle karşılaşılan problemler dikkate alındığında, finansal stres endeksinin belirlenmesi büyük önem taşımaktadır. Çalışma ile makine öğrenmesi yöntemleri kullanılarak finansal stres endeksi seviyesinin tahmin edilmesi amaçlanmaktadır. Bu amaçla finansal stres endeksinin haftalık zaman serileri, bağımsız ve hibrit modeller kullanılarak incelenmiştir. Yapay sinir ağları, bağımsız makine öğrenme modelleri olarak kullanılırken, hibrit modeller oluşturmak için bir ön işleme tekniği olarak dalgacık dönüşümü kullanılmıştır. Ayrıca, finansal stres endeksi tahminler

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6

Mazanoğlu, Kemal, and Elif Çağda Kandemir Mazanoğlu. "Artificial Neural Network Modelling of Cracked Beams." Afyon Kocatepe University Journal of Sciences and Engineering 17, no. 3 (2017): 1129–35. http://dx.doi.org/10.5578/fmbd.61866.

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7

ŞAHİN, Mustafa, Fuat BÜYÜKTÜMTÜRK, and Yüksel OĞUZ. "Light Quality Control with Artificial Neural Networks." Afyon Kocatepe University Journal of Sciences and Engineering 13, no. 2 (2013): 1–10. http://dx.doi.org/10.5578/fmbd.6222.

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8

KARLIK, Bekir, and Müh Saul . SARLI CEMEL. "Diagnosing Diabetes from Breath Odor Using Artificial Neural Networks." Turkiye Klinikleri Journal of Medical Sciences 32, no. 2 (2012): 331–36. http://dx.doi.org/10.5336/medsci.2011-22770.

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9

TURGUT, Bayram. "The Estimation of Gravity Values by the Back Propagation Artificial Neural Networks." Afyon Kocatepe University Journal of Sciences and Engineering 16, no. 3 (2016): 660–64. http://dx.doi.org/10.5578/fmbd.37325.

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10

Güllü, Mevlüt, Bayram Turgut, and Tamer Baybura. "The Comparison of Artifical Neural Networks and Kriging Interpolation Method fort he Geoid Height Determination." Afyon Kocatepe University Journal of Sciences and Engineering 16, no. 3 (2016): 674–78. http://dx.doi.org/10.5578/fmbd.40384.

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11

SUTCU, EVIN. "Estimation of Welded Manufacturing Operation Times with Matlab Artificial Neural Networks." Gazi Journal of Engineering Sciences 4, no. 1 (2018): 16–26. http://dx.doi.org/10.30855/gmbd.2018.04.01.003.

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12

Ergul, Hamdi. "Yapı endüstrisinde kullanılan sürdürülebilir ahşap malzemenin yapay sinir ağları ile ihtiyaç tahmini." Karaelmas Science and Engineering Journal 4, no. 2 (2014): 21–26. http://dx.doi.org/10.7212/zkufbd.v4i2.135.

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13

ORTAKAYA, SEFA, and REMZİ TUNTAS. "Estimation of Monthly Performance of Call Center Employees with Artificial Neural Networks Assistance." Gazi Journal of Economics and Business 4, no. 3 (2018): 161–72. http://dx.doi.org/10.30855/gjeb.2018.4.3.003.

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14

NARİN, Ömer Gökberk, Mevlüt GÜLLÜ, Tamer BAYBURA, and Bayram TURGUT. "Investigation of The Usability of Artificial Neural Networks (ANN) on 1/1000 Scale Cadastral Map Sheets Transformation." Afyon Kocatepe University Journal of Sciences and Engineering 18, no. 2 (2018): 575–80. http://dx.doi.org/10.5578/fmbd.67405.

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15

Benzer, Semra, and Recep Benzer. "Growth parameters with traditional and artificial neural networks methods of big-scale sand smelt (Atherina boyeri Risso, 1810)." Ege Journal of Fisheries and Aquatic Sciences 40, no. 2 (2023): 96–102. http://dx.doi.org/10.12714/egejfas.40.2.02.

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In this study, the growth parameters of big-scale sand smelt (Atherina boyeri Risso, 1810) in İznik Lake has been determined with traditional (length weight relationships (LWRs), von Bertalanffy (VB), condition factor (CF)) and modern approaches (Artificial Neural Networks - ANNs). A total of 635 specimens (44.84% female and 55.16% male) were collected from the local fisherman during the hunting season between April 2018 to April 2019. Mean fork length (FL) (mm, min-max), mean W (g, min-max) and mean CF (value, min-max) were estimated as 67.31 mm (40.10 - 97.77 mm), 2.57g (0.53 - 7.50 g), and

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16

Ahmet, Oğuz GÖK, YILDIZ Ceyhun, and ŞEKKELİ Mustafa. "Yapay Sinir Ağları Kullanarak Kısa Dönem Güneş Enerjisi Santrali Üretim Tahmini: Kahramanmaraş Örnek Çalışması." International Journal of Eastern Anatolia Science Engineering and Design (IJEASED) 1, no. 2 (2019): 186–95. https://doi.org/10.5281/zenodo.3511514.

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Türkiye coğrafi konumu nedeniyle büyük bir güneş enerjisi potansiyeline sahiptir ve ülkedeki Güneş Enerjisi Santrali (GES) kurulu gücü hızla artmaktadır. Fakat GES üretimlerindeki değişkenlik bu tesislerin elektrik şebeke sisteminde işletilmesini problem haline getirmektedir. Bu problemin giderilmesi için GES üretim tahminlerine ihtiyaç duyulmaktadır. Bu çalışmada GES üretimleri için bir tahmin sistemi önerilmiştir. Önerilen tahmin sisteminde Yapay Sinir Ağları (YSA) kullanılmıştır. YSA Levenberg-Marqu

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17

Güzel Güleç, Hacı, and Hüseyin Demirel. "ARTIFICIAL NEURAL NETWORK BASED PREDICTION OF INTENSITY OF INSOLATION IN THE CITY OF KASTAMONU USING METEOROLOGICAL DATA." e-Journal of New World Sciences Academy 12, no. 3 (2017): 114–21. http://dx.doi.org/10.12739/nwsa.2017.12.3.2a0118.

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18

Islak, Serkan, Mehmet Akkaş, Ünal Kaya, and Hacı Güzel Güleç. "ESTIMATION OF MECHANICAL AND PHYSICAL PROPERTIES OF Cu-TiC COMPOSITES BY ARTIFICIAL NEURAL NETWORKS (ANN)MODEL." e-Journal of New World Sciences Academy 12, no. 3 (2017): 122–29. http://dx.doi.org/10.12739/nwsa.2017.12.3.2a0119.

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19

BAL, Çağatay, and Ersin YILMAZ. "Modelling Right-Censored Data with Partially Linear Model and Feed Forward Neural Networks: A Methodological Study." Turkiye Klinikleri Journal of Biostatistics 14, no. 2 (2022): 90–102. http://dx.doi.org/10.5336/biostatic.2022-89354.

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20

Akkan, Tamer, Tanju Mutlu, and Eren Baş. "Forecasting sea surface temperature with feed-forward artificial networks in combating the global climate change: The sample of Rize, Türkiye." Ege Journal of Fisheries and Aquatic Sciences 39, no. 4 (2022): 311–15. http://dx.doi.org/10.12714/egejfas.39.4.06.

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The increase of the world population, especially in the global competition, together with the increasing use of fossil fuel resources to meet energy needs, leads to more greenhouse gases (more than one CO2, methane etc.) emissions and the global climate crisis. In this process, changes in meteorological events such as temperature, precipitation, and wind, attract attention moreover but when considered as a whole, we know that these negative changes in the ecosystem negatively affect many living groups. Sea Surface Temperature (SST) as measured meteorologically is the most important environment

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21

Baday, Şehmus. "MODELLING OF MAIN CUTTING FORCES WITH ARTIFICIAL NEURAL NETWORK IN TURNING OF SPHEROIDIZING HEAT TREATMENTED AISI 1050 STEEL." e-Journal of New World Sciences Academy 11, no. 1 (2016): 1–9. http://dx.doi.org/10.12739/nwsa.2016.11.1.2a0091.

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22

Sezgin, Cihangir Tevfik, Üna Kaya, and Mehmet Akkaş. "ESTIMATING WEARING RATE OF STEEL COATING SiC(P) BY USING TIG METHOD WITH ARTIFICIAL NEURAL NETWORKS." e-Journal of New World Sciences Academy 11, no. 4 (2016): 146–52. http://dx.doi.org/10.12739/nwsa.2016.11.4.2a0103.

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23

KÖKSAL, Özlem, and Emel TAŞÇI DURAN. "Doğum Ağrısının Algılanmasında ve Yansıtılmasında Kültürün Etkisinin İncelenmesi." Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi 12, no. 1 (2023): 155–66. http://dx.doi.org/10.37989/gumussagbil.908657.

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Bu araştırma ile vajinal doğum yapan kadınlarda doğum ağrısının algılanmasında ve yansıtılmasında kültürün etkisinin incelenmesi amaçlanmıştır. Bu araştırma 17.01.2013 – 31.05.2013 tarihleri arasında Şırnakta bir hastanenin doğumhanesinde yapılmıştır. Örnekleme, miadında, vajinal doğum yapan 150 gebe alınmıştır. Veri toplamada, gebelerin sosyodemografik, obstetrik ve kültürel özelliklerini içeren bir anket formu, doğum eyleminde gebenin tepkilerini içeren izlem formu kullanıldı. Gebelerin yaş ortalaması 27,39 ±6,58 olup, %94’ü Kürt etnik kökenlidir. Gebelerin %62,7’si geleneksel kurallara çok

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24

ŞAHİN, Nursel, Fatih TATBUL, Ahmet KUŞ, and Meral ÖZARSLAN YATAK. "Artificial Neural Network Modeling of Industrial Liquid Level Control." El-Cezeri Fen ve Mühendislik Dergisi, September 7, 2022. http://dx.doi.org/10.31202/ecjse.1132317.

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System modeling is a scientific method that combines theory with experimental studies and has an important place in research activities. With the system model, the data to be obtained through real tests and experiments are provided more economically in terms of cost and the critical points of the system are provided with time savings. Some system models are very difficult to obtain using only analytical equations and methods. At this point, artificial neural networks are an alternative way to model complex, uncertain, nonlinear systems. Artificial neural network is an artificial intelligence s

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25

Erdas, Cagatay Berke, Tunc Asuroglu, Koray Acici, and Hasan Ogul. "Comparison of Artificial Neural Networks and Genetic Programming Methods For Activity Recognition." Journal of Intelligent Systems with Applications, May 2, 2018, 62–66. http://dx.doi.org/10.54856/jiswa.201805019.

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With the widespread use of wearable sensors, the processing of raw data obtained from sensors has led to widely-used solutions to the problem of activity recognition. In this context, it is aimed to compare the performance of artificial neural network methods (ANN, RBFNN) and genetic programming (GP) methods over time, frequency and wavelet features extracted from the accelerometer data. The most successful classification performance achieved was 75.09% using 31 neurons in the hidden layer of the multilayer perceptron, using time attributes.

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26

Karabacak, Yunus Emre, Hamdi Tolga Kahraman, Levent Gumusel, and Cemal Yilmaz. "Detection and Classification of Ring Failures by Artificial Neural Networks in Bearings." Journal of Intelligent Systems with Applications, May 2, 2018, 31–35. http://dx.doi.org/10.54856/jiswa.201805011.

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An effective way to improve the efficiency and extend the life of the machines is to determine the failures of the bearings during operation. Early detection of bearing failures also has critical importance in terms of production costs. Various maintenance methods are used to prevent the failures. Despite all the precautions, unexpected failures can occur and production operations can be failed. This situation, apart from conventional methods, requires a novel determination and diagnostic technique. In this study, artificial intelligence based methods are applied and models are developed in or

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27

DEĞER, Ömer, and Emin SÜEL. "Comparison of Real Judo Competition Results with Artificial Neural Networks Method." Spor Eğitim Dergisi, July 21, 2022. http://dx.doi.org/10.55238/seder.1011913.

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In this study, it is aimed to predict Judo competition results with artificial neural networks. For this purpose, 21 different models were created with hyperparameters of the number of layers, number of neurons and optimization methods (SGD, RMSprop, Adam, Adadelta, Adagrad, Adamax, Nadam) in the artificial neural network. The sample of the study consists of 7758 athletes competing in international judo competitions between 2017:01-2021:03. 14 different attributes of each athlete were calculated from the data obtained from 53775 judo competitions held in this period. By sending the attributes

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28

DEMIR, VAHDETTIN, and ASLI ULKE KESKIN. "Height Modeling with Artificial Neural Networks (Samsun-Mert River Basin)." Gazi Journal of Engineering Sciences 6, no. 1 (2020). http://dx.doi.org/10.30855/gmbd.2020.01.05.

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29

Sayilgan, Ebru, and Savas Sahin. "Feature Extraction of ECG Signals using NI LabVIEW Biomedical Workbench and Classification with Artificial Neural Network." Journal of Intelligent Systems with Applications, May 2, 2019, 34–38. http://dx.doi.org/10.54856/jiswa.201905056.

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In this study, a data set containing normal and different heart beat types recorded by the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) was used for the detection of cardiac dysfunctions. In this data set, features were extracted using the LabVIEW Biomedical Workbench from the normal heartbeat and six different arrhythmia types. Obtained signals were evaluated by using Artificial Neural Network multiple classification method. Classification performances were compared before extracting the feature on the same data set. Classifier performances were evaluated by accuracy,

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30

EŞİDİR, Kamil Abdullah, Yunus Emre GÜR, Vahap YOĞUNLU, and Muhammed ÇUBUK. "Estimation of Monthly Brand New Car Sales in Turkey with ARIMA Method and Artificial Neural Networks (ANN)." Pamukkale University Journal of Business Research, August 22, 2022. http://dx.doi.org/10.47097/piar.1132101.

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In this study, the estimation of brand new car sales in Turkey was carried out with Artificial Neural Networks (ANN) from artificial intelligence-based estimation methods and ARIMA Method (One of the Time Series Analysis techniques). In the study, the dependent variable is “monthly brand new car registrations”. The independent variables are; “Monthly automobile exports (USD), monthly automobile imports (USD), monthly American Dollar Rate (TL), monthly Turkey’s exports (USD) and monthly Turkey’s imports (USD)” values. Using the monthly data obtained from the Turkish Statistical Institute (TUIK)

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31

GÜNGÖR, Güven, Aytaç AKÇAY, Savaş SARIÖZKAN, and Elif ÇELİK. "Comparison of Artificial Neural Networks, Random Forest Algorithm and Logistic Regression Analysis Performances in Classification of Effective Factors on Calf Diseases." Erciyes Üniversitesi Veteriner Fakültesi Dergisi, August 1, 2022. http://dx.doi.org/10.32707/ercivet.1142552.

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In this study, it is aimed to classify the factors affecting calf diseases with Artificial Neural Networks (YSA), Random Forest Algorithm (RO) and Logistic Regression Analysis (LR), to reveal the usability of these methods and to compare their performances. The research material consisted of the farm records of 54 calves kept in Erciyes Universi-ty, Agricultural Research and Application Center between 2018-2021. In the statistical analysis, the disease history of the calves was the dependent variable; calves gender, breed, birth season, maternal breed, and maternal lactation number were determ

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32

ERTUĞRUL, İrfan, and Atiyye BEKİN. "COMPERATIVE ANALYSES OF FORECASTING MODELS OF ARTIFICIAL NEURAL NETWORK AND TIME SERIES ANALYSES FOR SELECTED MAIN FOOD PRICES IN TURKEY." Kafkas Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 2016. http://dx.doi.org/10.9775/kauiibfd.2016.013.

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