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MOBRO: multi-objective battle royale optimizer

Taymaz Akan

Battle Royale Optimizer (BRO) is a recently proposed optimization algorithm that has added a new category named game-based optimization algorithms to the existing categorization of optimization algorithms. Both continuous and binary versions of this algorithm have already been proposed. Generally, optimization problems can be divided into single-objective and multi-objective problems. Although BRO has successfully solved single-objective optimization problems, no multi-objective version has been proposed for it yet. This gap motivated us to design and implement the multi-objective version of B ...Daha fazlası

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A hybrid firefly and particle swarm optimization algorithm applied to multilevel image thresholding

Taymaz Akan

There are many techniques for conducting image analysis and pattern recognition. This papers explores a way to optimize one of these techniques-image segmentation-with the help of a novel hybrid optimization algorithm. Image segmentation is mostly used for a semantic segmentation of images, and thresholding is one the most common techniques for performing this segmentation. Otsu's and Kapur's thresholding methods are two well-known approaches, both of which maximize the between-class variance and the entropy measure, respectively, in a gray image histogram. Both techniques were developed for b ...Daha fazlası

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Examination on the current conduction mechanisms of Au/n-Si diodes with ZnO-PVP and ZnO/Ag2WO4 -PVP interfacial layers

İlke Taşçıoğlu

This study reports a comparative characterization of Au/n-Si Schottky diodes/contacts (SDs) with hydrothermally synthesized ZnO-PVP and ZnO/Ag2WO4-PVP interfacial layers, which outperforms conventional metal-semiconductor Schottky diode structures. This characterization is important because these structures outperform traditional metal-semiconductor Schottky diodes due to the presence of an interfacial layer, allowing barrier height control, surface passivation, and leakage current reduction. Based on the thermionic emission (TE) theory assumed to be the dominant current mechanism across, SDs ...Daha fazlası

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Differential Diagnosis of Diabetic Foot Osteomyelitis and Charcot Neuropathic Osteoarthropathy with Deep Learning Methods

Gökalp Tulum

Our study aims to evaluate the potential of a deep learning (DL) algorithm for differentiating the signal intensity of bone marrow between osteomyelitis (OM), Charcot neuropathic osteoarthropathy (CNO), and trauma (TR). The local ethics committee approved this retrospective study. From 148 patients, segmentation resulted in 679 labeled regions for T1-weighted images (comprising 151 CNO, 257 OM, and 271 TR) and 714 labeled regions for T2-weighted images (consisting of 160 CNO, 272 OM, and 282 TR). We employed both multi-class classification (MCC) and binary-class classification (BCC) approaches ...Daha fazlası

Erişime Açık

Multi-modal Battle Royale optimizer

Taymaz Akan

Multimodal optimization poses a challenging problem in the field of optimization as it entails the discovery of multiple local and global optima, unlike unimodal optimization, which seeks a single global solution. In recent years, the significance of addressing multimodal optimization challenges has grown due to the real-world complexity of many problems. While numerous optimization methods are available for unimodal problems, multimodal optimization techniques have garnered increased attention. However, these approaches often grapple with a common issue: the determination of the niching param ...Daha fazlası

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Multilevel image thresholding with multimodal optimization

Taymaz Akan

Thresholding method is one of the most popular approaches for image segmentation where an objective function is defined in terms of threshold numbers and their locations in a histogram. If only a single threshold is considered, a segmented image with two classes is achieved. On the other hand, multiple classes in the output image are created with multilevel thresholding. Otsu and Kapur's procedures have been conventional steps for defining objective functions. Nevertheless, the fundamental problem with thresholding techniques is the determination of threshold numbers, which must be selected by ...Daha fazlası

Süresiz Ambargo

A multimodal butterfly optimization using fitness-distance balance

Taymaz Akan

Due to the multimodal nature of real-world optimization problems, in recent years, there has been a great interest in multi-modal optimization algorithms. Multimodal optimization problems involve identifying multiple local/global optima. Niching techniques have been widely used to tackle multi-modal optimization problems. Most of the existing niching methods either require predefined niching parameters or extra information about the problem space. This paper presents a novel multimodal algorithm based on Butterfly Optimization Algorithm, which is constructed using the Fitness-Distance Balance ...Daha fazlası

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