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With the help of ability to imitate the biological nervous system, Spiking Neural Networks (SNNs) architectures have become popular recently. In order to benefit at the maximum level from the low power consumption, event-based structure and parallelization fea…

In this study, the elimination of zero diffraction order and twin image from three dimensional reconstructed images in digital holography and the image enhancement are desired to achieve in a short time by using hybrid methods. In addition, the brightness of t…

In this paper, signal recognition system is proposed for classification of soil types and buried object by using feature extraction and artificial neural networks. Using GprMax simulation program, 300 GPR A scan signals were obtained for different ground plane…

Bu çalışmada Yapay Bağışıklık Sistemine(YBS) dayalı Klonal Seçim Algoritması'nın (KSA) Matlab ortamında yazılımı gerçekleştirilmiştir. Ayrıca KSA'na koşul tabanlı bir yapı eklenerek geliştirilmiştir. Geliştirilen Koşul-Tabanlı Klonal Seçim Algoritması (KT-KSA)…

Complexity in the behavior of asphalt binders are further escalated with geopolymer (fly ash and the alkali liquid) modification thus, making it difficult to predict the performance of the binder accurately. This study employs artificial neural network model…

Elektromiyografi, kas aktivitesi sonucunda meydana gelen biyolojik işaretlerin ölçülmesine olanak sağlayan invaziv olmayan bir yöntemidir. Yüzey ve iğne elektromiyografisi olarak uygulama amacına göre iki şekilde kullanılmaktadır.  Bu çalışmada internet üzerin…

The integration of increasing renewable energy-based energy production into the existing electricity grid has become of great importance. The biggest difficulty to integration into the power grid is variability and discontinuity of wind energy. To deal with th…

Handwritten Signature Recognition (HSR) is a vital task in document authentication and verification systems. This paper proposes a novel approach for offline HSR leveraging pre-trained Convolutional Neural Network (CNN) models. CNNs have demonstrated remarkabl…

The aim of this study is to forecast installed wind power which is a one of the renewable energy resources in Turkey for the year of 2017 based on artificial neural network method using the normalized last ten-year data. An artificial neural network has been c…

Traffic flow forecasting has an important place in designing a successful intelligent transportation system. The success of the forecasting is related to the accuracy and timely acquisition of the traffic flow data. The inadequacy in the number of data has led…

Neural Network has been used in a number of scientific fields including medical diagnosis. It is clear that classification is one of the main challenges in any medical diagnosis. However, the drawbacks of conventional neural network classifier are summarized a…

In this study, the effect of using a mixture of butanol and diesel fuel in a small diesel engine on engine performance and exhaust emissions is modeled. A comparison has been made with artificial neural networks, which is an up-to-date method, and multiple l…

This paper describes a laboratory application for the forecasting the dielectric properties, using an artificial neural network embedded in a microprocessor. The dielectric permittivity and loss factor of the insulation material were determined as a function o…

Yapay sinir ağları makine öğrenmesi alanında birçok problemin çözümünde sıklıkla kullanılmaktaydı. Fakat “Yapay Zeka Kışı” olarak da adlandırılan dönemde ilk olarak donanımsal kısıtlamalar ve diğer problemler sebebiyle bu alandaki çalışmalar durma noktasına ge…

Complex-valued artificial neural network (CVANN) has been developed to process data with complex numbers directly. In a CVANN the weights, threshold, inputs and outputs are all complex numbers. The convergence of the CVANN back propagation algorithm depending …

Network security is becoming more and more important as a result of the growing use of the internet and technological developments. Intrusion Detection Systems (IDS) are utilized to detect attacks, preferably by monitoring real-time events. Therefore, they hol…

The increasing world population has increased the demand for food. Many threats such as agricultural land use, environmental impacts, global warming and drought risks necessitate industrialization of agricultural production and optimum utilization of existing …

Researchers attention on the optimization methods to solve several applications increases recently by the advances in the technological field. The Artificial Bee Colony algorithm that has been quite popular during the recent years is firstly used in this study…

It is important to determine the initial level of failures of induction motors used in many industrial applications. The sudden stops of the system can be prevented with the pre-detection of the fault. The experiment mechanism was established to detect mechani…

Deep learning is a machine learning sub-field that uses deep neural networks. Instead of customized algorithms for each study in this field, it is aimed to cover the wider data set of solutions based on learning the data. Deep learning is a promising approach …