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Öğe Bireylerin Koroner Arter Hastalığı Risk Seviyesinin Bulanık Uzman Sistem Yaklaşımı İle Belirlenmesi(2022) Teke, ÇağatayKoroner Arter Hastalığı (KAH) dünya genelinde insanların hayatını kaybetmesine sebep olan en önemli hastalıklardan biridir. Tıp alanında yaşanan gelişmeler bu hastalığın tedavisini kolaylaştırsa da risk faktörlerinin belirlenmesi ve değerlendirilmesinde hala birtakım yetersizlikler söz konusudur. Bu çalışmada, KAH ile ilgili yaygın belirti ve şikayetleri olan bireyler göz önüne alınarak tanıda kullanılan çeşitli risk faktörleri belirlenmiştir. Ayrıca bulanık uzman sistem yöntemi kullanılarak bireylerin KAH risk düzeylerini tespit etmek amacıyla bir yapay zeka sistemi geliştirilmiştir. Tasarlanan sistem kural tabanlı olup, bu kural tabanı yapısı tıp uzmanlarından edinilen bilgilerle oluşturulmuştur. Sistem, bireylerin hastalık riskini azaltmak için kendi kendine risk değerlendirmesi ve özelleştirilmiş öneriler sunmaktadır. Bu sayede koroner arter hastalığından muzdarip kişilerin sayısındaki artış önlenebilir veya geciktirilebilir.Öğe Bulanık AHP ve Bulanık TOPSIS Yöntemleri ile Sakarya İlinin Yatırım Öncelikli Sektörlerinin Belirlenmesi(Bayburt University, 2018) Kiraz, Alper; Gençer, Nilay; Taş, Mehmet; Teke, ÇağatayBelirli bir bölgede yapılacak olan yatırım için, yatırımın geri dönüş performansı gibi unsurlar üzerindeki etkileri nedeniyle öncelikli sektörün belirlenmesi önemli karar problemlerinden biridir. Bu kapsamda gerçekleştirilen çalışmanın temel amacı, Sakarya ili için sektörlerin öncelik sıralarının belirlenmesidir. Bu amaca yönelik yapılan çalışmada Bulanık AHP ve Bulanık TOPSIS yöntemleri kullanılmıştır. Öncelikli alanların belirlenmesinde etkili olan 19 kriterin ağırlıklarını belirlemek için Bulanık AHP yöntemi kullanılırken, belirlenen 16 adet alternatif arasında sıralama yapmak için Bulanık TOPSIS yöntemi kullanılmıştır. Buna göre yatırım öncelikli sektörlerin belirlenmesinde etkili olan en önemli üç kriter "pazar", "teşvik ve destekler" ve "hammaddeye yakınlık" olarak belirlenirken "otomotiv ve yan sanayi", "demir-çelik metal işleme" ve "ziraat-tarım ve hayvancılık" sektörleri Sakarya ili için öncelikli sektörler olarak belirlenmiştir.Öğe Çimento Üretim Sürecinde Makine Arıza Sürelerinin Tahmini Üzerine Bir Uygulama(Bayburt Üniversitesi, 2024) Teke, Çağatay; İpek, MümtazBu çalışma, çimento üretim sürecindeki makinelerin arıza sürelerini tahmin etmemizi sağlayacak bir model geliştirmeyi amaçlamaktadır. Makine arızalarının bilinmesi, üretimi artırmak ve bakım maliyetlerini en aza indirmek için makinelerin bakımında çok önemlidir. Bu bağlamda, arıza dağılımlarını değerlendirmek için Weibull dağılımı, En Küçük Kareler (LS) yöntemi ve Maksimum Olabilirlik Tahmini (MLE) yöntemi uygulanmıştır. Bu çalışmada 167 makine arıza verisi kullanılmış ve Minitab yazılımı ile analiz edilmiştir. Arıza sürelerinin Weibull dağılımını takip ettiği sonucuna varılmış ve uygunluğu kontrol etmek amacıyla dağılımın parametrelerini tahmin etmek için LS ve MLE yöntemleri kullanılmıştır. Böylece LS yöntemi uygulandığında ? = 2.07 ve ? = 971.7, MLE yöntemi uygulandığında ise ? = 2.17 ve ? = 966 olarak elde edilmiştir. Bu değerlerin oldukça yakın olduğu ve her iki yöntemin de neredeyse aynı sonuçları verdiği görülmüştür.Öğe Determining Amounts of Energy Saver Devices in an Electronic Industry Using Fuzzy Linear Programming(Özer UYGUN, 2018) Teke, Çağatay; Kiraz, AlperRapid and accurate decision making is not only important for people but also for organizations. However, uncertainty makes decision making difficult. Fuzzy logic approach is deal with uncertainty situations. Namely, fuzzy logic is a precise logic of uncertainty and approximate reasoning. Besides, Fuzzy Linear Programming (FLP) is also known as a strategy that can take into consideration to fuzziness. Determining amounts of production is one of the most important factors effecting the profitability level of enterprises. The aim of this study which is prepared since classical mathematical programming models are inadequate to examine situations that consist of uncertainty; is to bring up how FLP model for providing the best decision making under fuzzy environments can be used at determining amounts of energy saver devices. Required data is obtained and the problem is figured out via Zimmerman approach which is one of the approaches for FLP. In this way, problems that may occur such as cost, waste of time, overstock and customer loss will be prevented. As a result, the solution gives the amount of production for each energy saver device in order to get optimal solution for profit maximizing. This study makes a contribution to practicality of FLP, by supplying a wider moving area than classical set theory to decision makers.Öğe Green Supplier Assessment with Fuzzy Expert System Approach(2024) Teke, ÇağatayToday, reasons such as increasing pollution on a global extent and limited raw material resources are increasing the interest in green supply chain management (GSCM). GSCM includes the processes starting from the very beginning of the production process of a product, completing the production, delivering the product to the customer, and recycling the product at the end of its useful life. Its main purpose is to eliminate or minimize the damages caused to the environment in all of these processes. In order to achieve this goal, it has great importance to assess the suppliers, which are one of the most important components of the production process, in terms of becoming a green supplier. In this study, a fuzzy expert system model has been developed to assess the green suppliers based on green production technology, environmental management system, pollution control, product cost, quality, and lead time criteria. Mean Square Error (MSE) and coefficient of determination (R2) have been calculated to measure the performance of the developed model. These calculated values show that the green supplier assessment performance of the developed model is quite high.Öğe Green Supplier Assessment with Fuzzy Expert System Approach(2024) Teke, ÇağatayToday, reasons such as increasing pollution on a global extent and limited raw material resources are increasing the interest in green supply chain management (GSCM). GSCM includes the processes starting from the very beginning of the production process of a product, completing the production, delivering the product to the customer, and recycling the product at the end of its useful life. Its main purpose is to eliminate or minimize the damages caused to the environment in all of these processes. In order to achieve this goal, it has great importance to assess the suppliers, which are one of the most important components of the production process, in terms of becoming a green supplier. In this study, a fuzzy expert system model has been developed to assess the green suppliers based on green production technology, environmental management system, pollution control, product cost, quality, and lead time criteria. Mean Square Error (MSE) and coefficient of determination (R2) have been calculated to measure the performance of the developed model. These calculated values show that the green supplier assessment performance of the developed model is quite high.Öğe Implementation of Fuzzy Linear Programming Approach for More Accurate Demand Forecasting in a Make-to-Stock Company(2023) Teke, ÇağatayDemand forecasting is of crucial importance for make-to-stock companies because product demand is uncertain and it changes with time. Fuzzy linear programming (FLP) can be an optimum approach for such uncertain situations. In this study, the FLP model was used for more accurate demand forecasting in a make-to-stock company. Demand forecasting study was carried out according to the FLP method and linear programming (LP) method. Solutions of FLP and LP were compared in terms of imputed shortage cost, inventory carrying cost, and net profit. Results show that the applied FLP method is more advantageous than LP as it provides a 67% decrease in costs and a 15% increase in net profit.Öğe Implementation of Fuzzy Linear Programming Approach for More Accurate Demand Forecasting in a Make-to-Stock Company(2023) Teke, ÇağatayDemand forecasting is of crucial importance for make-to-stock companies because product demand is uncertain and it changes with time. Fuzzy linear programming (FLP) can be an optimum approach for such uncertain situations. In this study, the FLP model was used for more accurate demand forecasting in a make-to-stock company. Demand forecasting study was carried out according to the FLP method and linear programming (LP) method. Solutions of FLP and LP were compared in terms of imputed shortage cost, inventory carrying cost, and net profit. Results show that the applied FLP method is more advantageous than LP as it provides a 67% decrease in costs and a 15% increase in net profit.Öğe Prediction of gamma ray spectrum for 22Na source by feed forward back propagation ANN model(Elsevier Ltd, 2023) Teke, Çağatay; Akkurt, Iskender; Arslankaya, Seher; Ekmekci, I.; Güno?lu, KadirThe radiation has been used in a variety of different fields since its discovery and thus its measurement becomes vital in these industries. Different type detector may be used to measure gamma rays depends on the purposes of measurements. Gamma ray energy spectrum is an important to determine either elemental analysing of a sample or radiation shielding purposes. On the other hand, Artificial Neural Network (ANN) may be used to predict and analysing of gamma-ray spectrum. In this study, gamma ray spectrum from 22Na source detected in NaI (Tl) detector was estimated by ANN. There have been installed ten different ANN models to find the network structure that produces the best predictive value for the gamma ray spectrum NaI (Tl) Detector. Estimation study has been continued with the ANN model with be possessed of lowest error value. ANN model was created by using energy, distance and gamma-rays energy spectrum (called Io) values. In the ANN model developed using the feed forward back propagation algorithm, were used artificial neurons two in the input layer, ten in the hidden layer and one in the output layer. For the case of present work, the experimental data was used 70% for education, 20% for validation and 10% for testing. The estimated values obtained with the ANN model were compared with the experimental results and a good correlation has been found between them (R2 = 0.99). © 2022 Elsevier LtdÖğe PREDICTION OF TURKEY'S COTTON SOCK EXPORTS TO GERMANY USING DEEP LEARNING APPROACH(Chamber of Textile Engineers, 2024) Özbek, Ahmet; Teke, ÇağatayCotton socks are a strategic export product for Turkey. Therefore, the aim of this study is to forecast Turkey's exports to Germany, the world's largest cotton socks market. In order to achieve this objective, the determinants of exports were identified by analysing the literature. Then, expert opinion was sought to determine the importance of these factors for Turkey's cotton socks exports to Germany. Using the deep learning model created from the factors determined as a result of the expert opinion, the prediction of the export of Turkish socks to Germany was realised. A success rate of 96% was achieved with the prediction. © (2023), (Chamber of Textile Engineers). All Rights Reserved.
