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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…

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…

Wireless sensor network (WSN) is a distributed system usually comprising a set of autonomous sensors nodes. These sensors are physically small in size and are capable to communicate with each other and capable of conveying data to recipients. In a large number…

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…

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…

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…

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…

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 …

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…

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…

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 …

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 …

Seismic data is a critical source for examining and understanding subsurface structures. It is used in various fields such as oil exploration, geological research, mining, underground infrastructure planning, environmental monitoring, and conservation. The ana…

The COVID-19 pandemic has necessitated the development of rapid, accurate, and automated diagnostic tools to assist healthcare professionals in patient screening and management. This comprehensive study presents a detailed comparative analysis of ten state-of-…

In recent years, computer vision has taken great strides in understanding and recognition the visual scenes together with deep learning technologies. Object recognition is one of the key areas of the computer vision applications. It is mainly concerned with re…

Today, artificial intelligence, which has been used in all areas of life, has been used effectively in real estate housing market researches. Artificial intelligence, one of the techniques of artificial intelligence, inspired by the working principle of human …

Social networks are formed from interactions of peoples. Measuring the degree of those relationships requires interpreting connectivity of vertices and extracting information from it. Generally individuals form smaller sub-communities in those networks. Identi…

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…

Palmprint recognition (PR) has garnered significant interest due to its distinctive characteristics and potential applications as a robust and secure biometric authentication (BA) method across various domains. This paper introduces a novel approach to enhance…