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Öğe Comparison of classification performance of kNN and WKNN algorithms(Selçuk Üniversitesi, 2021) Tarakci, Fatih; Ozkan, Ilker AliIn this study, K nearest neighbor (kNN) algorithm which is the most popular and widely used among the machine learning classification algorithms and the weighted kNN (WKNN) algorithm which takes the weight of the feature index into consideration, are used. As the weighting method, a weighting is made by taking the inverse of the distance squared (w = 1 / d2 ). The confusion matrix of the data sets was created by applying the algorithms to five data sets via MATLAB program and the classification success was compared by conducting performance measurements of algorithms. It was observed that in two of the five data sets used in the study kNN algorithm turned out to make a more successful classification than WKNN while in three data sets the WKNN algorithm performed a more successful classification than the kNN.Öğe The control of magnetic filters by FPGA based fuzzy controller(SILA SCIENCE, 2012) Ozkan, Ilker Ali; Saritas, Ismail; Herdem, SaadetdinOne of the most effective methods to clean magnetic particles in industrial liquids is magnetic filtration. Magnetic filters (MF) are being used increasingly since they can work under various conditions like high temperature and radioactivity. However, there are many factors like particle concentration and flow speed that affect magnetic filter performance (MFP). In this study, a portable, compact MF kit that cleans micron-sized magnetic particles and is suitable for industrial purposes was designed and realized. A FPGA based fuzzy control system that considers the factors which influence MF performance was developed and integrated with MF kit. With this control system both the MF performance is kept at maximum and MF can clean itself. Thus, besides an effective filtration process which increases quality, sustainability of production and energy save is achieved.Öğe The effects of fuzzy control of magnetic flux on magnetic filter performance and energy consumption(PERGAMON-ELSEVIER SCIENCE LTD, 2010) Saritas, Ismail; Ozkan, Ilker Ali; Herdem, SaadetdinMagnetic filters are used effectively in many industrial areas to clean up technological liquids and gases from micron and submicron size magnetic particles. Performance of the magnetic filter is affected by technological parameters like flow rate of the industrial liquid and concentration and flux magnitude of the magnetic filter. These parameters exhibit differences depending on the field of work. Controlling of magnetic filters without regard to these parameters has disadvantages such as low filter performance, ineffectiveness in parameter changes and high energy consumption. To remove these disadvantages, an adaptive fuzzy control system which considers these technological parameters was designed and realized. When the realized filter is compared to the filter that ignores technological parameters, it is observed that energy can be saved at a rate of 68% annually. (C) 2010 Elsevier Ltd. All rights reserved.Öğe Estimating of compressive strength of concrete with artificial neural network according to concrete mixture ratio and age(2016) Ozkan, Ilker Ali; Altın, MustafaCompressive strength of concrete is one of the most important elements for an existing building and a new structure to be built. While obtaining the desired compressive strength of concrete with an appropriate mix and curing conditions for a new structure, with nondestructive testing methods for an existing structure or by taking core samples the concrete compressive strength are determined. One of the most important factors that affects the concrete compressive strength is age of concrete. In this study, it is attempted to estimate compressive strength, modelling Artificial Neural Networks (ANN) and using different mixture ratios and compressive strength of concrete samples at different ages. In accordance with obtained data's in the estimation of concrete compressive strength, ANN could be used safelyÖğe FPGA-based self-organizing fuzzy controller for electromagnetic filter(SPRINGER, 2017) Ozkan, Ilker Ali; Herdem, Saadetdin; Saritas, IsmailElectromagnetic filters (EMF) are used to clean magnetic particles in industrial liquids which play important roles to sustain the high-quality material production in industrial fields. In this study, an FPGA-based adaptive fuzzy controller is realized to sustain high performance of an EMF. An experiment is performed by using realized adaptive controller on an EMF set. The results obtained from the experiment are compared with the results of the conventional fuzzy controller. It is observed that adaptive fuzzy controller is performed better than the conventional fuzzy controller.Öğe Skin Lesion Classification using Machine Learning Algorithms(2017) Ozkan, Ilker Ali; Koklu, MuratMelanoma is a deadly skin cancer that breaks out in the skin’s pigment cells on the skin surface. Melanoma causes 75% of the skin cancer-related deaths. This disease can be diagnosed by a dermatology specialist through the interpretation of the dermoscopy images in accordance with ABCD rule. Even if dermatology experts use dermatological images for diagnosis, the rate of the correct diagnosis of experts is estimated to be 75-84%. The purpose of this study is to pre-classify the skin lesions in three groups as normal, abnormal and melanoma by machine learning methods and to develop a decision support system that should make the decision easier for a doctor. The objective of this study is skin lesions based on dermoscopic images PH2 datasets using 4 different machine learning methods namely; ANN, SVM, KNN and Decision Tree. Correctly classified instances were found as 92.50%, 89.50%, 82.00% and 90.00% for ANN, SVM, KNN and DT respectively. The findings show that the system developed in this study has the feature of a medical decision support system which can help dermatologists in diagnosing of the skin lesions
