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A novel seismic vulnerability assessment for the urban roadway by using interval valued fermatean fuzzy analytical hierarchy process

Bahar Yalçın Kavuş | Tolga Kudret Karaca

Seismic activity poses significant challenges to urban road infrastructure, often resulting in road closures due to the combined effects of damaged buildings and affected road networks. In contrast, the resilience of roads is crucially important for all kinds of relief activities after an earthquake in this context, this study outlines a methodological framework for assessing the vulnerability of urban road infrastructure to seismic activity. By integrating various criteria within an Interval-valued Fermatean fuzzy Analytic Hierarchy Process framework, the approach offers a comprehensive analy ...Daha fazlası

Makale 2024 Natural Hazards 13 Görüntülenme

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Morphology for hexagonal image processing: a comprehensive simulation analysis

Sajjad Nematzadeh

Morphological operators for binary and grayscale images are commonly used to eliminate noise, recognize contours or specific structures, and arrange shapes in image processing for physiological modeling and biomechanics applications. Even though morphology has been substantially developed in square-pixel- based-image-processing (SIP), no effort has been made to construct morpho- logical operators in hexagonal-pixel-based-image-processing (HIP) yet. In this paper, we transform basic SIP-domain-morphological operators such as dilation, erosion, closing, and opening into HIP-domain and compare th ...Daha fazlası

Makale 2024 IAES International Journal of Artificial Intelligence 3 Görüntülenme

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Türkiye’de Rüzgâr Enerjisinin Mevcut Durumu ve Geleceği

Vedat Esen

Yenilenebilir enerji kaynakları, fosil yakıtların yakın zamanda tükeneceğinin öngörülmesi ve çevreye olan zararları nedeniyle tüm dünyada olduğu gibi Türkiye’de de elektrik enerjisi üretimi için alternatif olmaya başlamış ve bu konuda çalışmalar hız kazanmıştır. Yenilenebilir enerji kaynakları içerisinde, büyük miktarlarda enerji üretimine imkân vermesi nedeniyle öne çıkan rüzgâr enerjisi diğer enerji kaynaklarına göre tercih edilir duruma gelmiştir. Rüzgâr enerjisi teknolojilerinin gelişmesi ile birlikte coğrafi koşulları uygun olan ülkeler, yatırımlarını ağırlıklı olarak rüzgâr enerjisine ya ...Daha fazlası

Makale 2022 IGSCONG’22 75 Görüntülenme

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Design of Hybrid Controller for Automatic Voltage Regulator

Güngör Bal

Synchronous generators are still the main machines in the production of electrical energy. Changing the excitation current and the rotation speed easily adjust their output voltage and frequency. Since synchronous generators are operated with the grid, the output voltage and frequency must be fixed. Various control systems are used in Automatic Voltage Regulators for adjusting the voltage. In this study, a hybrid controller structure proposed and it operates in MATLAB / Simulink program. The simulation results of the proposed AVR is compared with PID adjusted by Artificial Bee Colonies algorit ...Daha fazlası

Makale 2023 Journal Of Polytechnic-Politeknik Dergisi26 ( 1 ) , pp. 1 - 207 41 Görüntülenme

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Automatic personality prediction: an enhanced method using ensemble modeling

Taymaz Akan

Human personality is significantly represented by those words which he/she uses in his/her speech or writing. As a consequence of spreading the information infrastructures (specifically the Internet and social media), human communications have reformed notably from face to face communication. Generally, Automatic Personality Prediction (or Perception) (APP) is the automated forecasting of the personality on different types of human generated/exchanged contents (like text, speech, image, video, etc.). The major objective of this study is to enhance the accuracy of APP from the text. To this end ...Daha fazlası

Makale 2022 Neural Computing & Applications34 ( 21 ) , pp. 1 - 18389 87 Görüntülenme

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PV Cells and Modules Parameter Estimation Using Coati Optimization Algorithm

Cevat Rahebi

In recent times, there have been notable advancements in solar energy and other renewable sources, underscoring their vital contribution to environmental conservation. Solar cells play a crucial role in converting sunlight into electricity, providing a sustainable energy alternative. Despite their significance, effectively optimizing photovoltaic system parameters remains a challenge. To tackle this issue, this study introduces a new optimization approach based on the coati optimization algorithm (COA), which integrates opposition-based learning and chaos theory. Unlike existing methods, the C ...Daha fazlası

Makale 2024 energies17 ( 7 ) 34 Görüntülenme

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A longitudinal case study on Nexus transformation: Impact on productivity, quality, and motivation

Selami Bağrıyanık

A longitudinal case study on Nexus transformation: Impact on productivity, quality, and motivation

Makale 2023 Wiley 23 Görüntülenme Süresiz Ambargo

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Battle royale optimizer for training multi-layer perceptron

Taymaz Akan

Artificial neural network (ANN) is one of the most successful tools in machine learning. The success of ANN mostly depends on its architecture and learning procedure. Multi-layer perceptron (MLP) is a popular form of ANN. Moreover, backpropagation is a well-known gradient-based approach for training MLP. Gradient-based search approaches have a low convergence rate therefore, they may get stuck in local minima, which may lead to performance degradation. Training the MLP is accomplished based on minimizing the total network error, which can be considered as an optimization problem. Stochastic op ...Daha fazlası

Makale 2021 Evolving Systems13 ( 4 ) , pp. 5 - 575 111 Görüntülenme Süresiz Ambargo

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Origin of frequency and voltage dependent negative dielectric properties in the Al/p-Si Schottky diodes with (Cd0.3Zn0.7O) interfacial layer in the wide range of frequency and voltage

İlke Taşçıoğlu

The real and imaginary parts of complex-dielectric (ε′ , ε’’) and electric-modulus (M′ , M′′), dielectric loss tangent (tanδ), and conductivity (σ) values of Al/(Cd0.3Zn0.7O)/p-Si Schottky Diode (SD) were obtained from capacitance/conductance vs. voltage/frequency (C/G-V-f) plots. Negative dielectric (ND) was observed under 50 kHz at about 3.5 V and the increase in the ε’’ results from a drop in ND with increasing voltage, also known as inductive behavior. The rise in σac at high frequencies causes the eddy-current to grow, which in turn causes the ε” or tanδ to increase. While the relaxation ...Daha fazlası

Makale 2023 PHYSICA B-CONDENSED MATTER665 , pp. 1 - 9 31 Görüntülenme

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Hybrid model-based prediction of biomass density in case studies in Turkiye

Buket İşler

Growing global concern over natural resource degradation due to urbanisation and population growth emphasizes the critical need for innovative solutions. Addressing this imperative, our study pioneers the integration of cutting-edge artificial intelligence (AI) methods to investigate crucial changes in vegetation density. In this context, a hybrid model, which harmoniously integrates conventional artificial neural network (ANN) models with the innovative Wavelet-ANN (W-ANN) approach, was employed in two case pilot areas, namely on Alanya in Antalya and Iznik in Bursa, Turkiye, renowned for the ...Daha fazlası

Makale 2024 Ecological Informatics79 8 Görüntülenme

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Effective test-data generation using the modified black widow optimization algorithm

Mahsa Torkamanıan Afshar

Software testing is one of the software development activities and is used to identify and remove software bugs. Most small-sized projects may be manually tested to find and fix any bugs. In large and real-world software products, manual testing is thought to be a time and money-consuming process. Finding a minimal subset of input data in the shortest amount of time (as test data) to obtain the maximal branch coverage is an NP-complete problem in the field. Different heuristic-based methods have been used to generate test data. In this paper, for addressing and solving the test data generation ...Daha fazlası

Makale 2024 Signal, Image and Video Processing 7 Görüntülenme

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Cervical cancer risk assessment using machine learning integrated fuzzy MCDM methodology

Fatih Şahin

Cervical cancer is entirely preventable if diagnosed at an early stage; however, the current rate of cervical cancer screening participation is not very adequate, and early detection approaches are still open and demanding. Evaluating the risk levels of potential patients in a practical and economic way is crucial to direct risky candidates to screening and establishing potential treatments to conquer the disease. In this study, a machine learning-integrated fuzzy multi-criteria decision-making (MCDM) methodology is proposed to assess the cervical cancer risk levels of patients. In this contex ...Daha fazlası

Makale 2024 Journal of Intelligent and Fuzzy Systems46 ( 2 ) , pp. 4 - 4592 27 Görüntülenme Süresiz Ambargo