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Doktor Öğretim Üyesi Taymaz AkanMühendislik Fakültesi/Yazılım Mühendisliği Bölümü/Yazılım Mühendisliği Pr. /
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BinBRO: Binary Battle Royale Optimizer algorithm

Taymaz Akan

Stochastic methods attempt to solve problems that cannot be solved by deterministic methods with reasonable time complexity. Optimization algorithms benefit from stochastic methods; however, they do not guarantee to obtain the optimal solution. Many optimization algorithms have been proposed for solving problems with continuous nature; nevertheless, they are unable to solve discrete or binary problems. Adaptation and use of continuous optimization algorithms for solving discrete problems have gained growing popularity in recent decades. In this paper, the binary version of a recently proposed ...Daha fazlası

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A memetic animal migration optimizer for multimodal optimization

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Unimodal optimization algorithms can find only one global optimum solution, while multimodal ones have the ability to detect all/most existing local/global optima in the problem space. Many practical scientific and engineering optimization problems have multiple optima to be located. There are a considerable number of optimization approaches in the literature to address the unimodal problems. Although multimodal optimization methods have not been studied as much as the unimodal ones, they have attracted an enormous amount of attention recently. However, most of them suffer from a common nichin ...Daha fazlası

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A multi-modal bacterial foraging optimization algorithm

Taymaz Akan

In recent years, multi-modal optimization algorithms have attracted considerable attention, largely because many real-world problems have more than one solution. Multi-modal optimization algorithms are able to find multiple local/global optima (solutions), while unimodal optimization algorithms only find a single global optimum (solution) among the set of the solutions. Niche-based multi-modal optimization approaches have been widely used for solving multi-modal problems. These methods require a predefined niching parameter but estimating the proper value of the niching parameter is challengin ...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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Multi-circle Detection Using Multimodal Optimization

Taymaz Akan

Object and shape detection in digital image were one of the hot topic over the last two decades. Especially automatic multi circle detection has received more attention over last years. Hough transform (HT) is a well-known and most popular method for lines and circles detection. However, HT has huge computational complexity expense. This paper proposed a new successful heuristic method to reduce computation time and improve the speed of HT for circle detection. In this proposed method the edges information of the image is obtained by means of Robert edge detection. Then, multimodal particle sw ...Daha fazlası

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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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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

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Battle Royale Optimizer for solving binary optimization problems

Taymaz Akan

Battle Royale Optimizer (BRO) is a recently proposed metaheuristic optimization algorithm used only in continuous problem spaces. The BinBRO is a binary version of BRO. The BinBRO algorithm employs a differential expression, which utilizes a dissimilarity measure between binary vectors instead of a vector subtraction operator, used in the original BRO algorithm to find the nearest neighbor. To evaluate BinBRO, we applied it to two popular benchmark datasets: the uncapacitated facility location problem (UFLP) and the maximum-cut (Max-Cut) graph problems from OR-Library. An open-source MATLAB im ...Daha fazlası

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Text‑based automatic personality prediction: a bibliographic review

Taymaz Akan

Personality detection is an old topic in psychology and automatic personality prediction (or perception) (APP) is the automated (computationally) forecasting of the personality on diferent types of human generated/exchanged contents (such as text, speech, image, and video). The principal objective of this study is to ofer a shallow (overall) review of natural language processing approaches on APP since 2010. With the advent of deep learning and following it transfer-learning and pre-trained model in NLP, APP research area has been a hot topic, so in this review, methods are categorized into th ...Daha fazlası

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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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Battle royale optimizer for multilevel image thresholding

Taymaz Akan

Image segmentation, the process of partitioning an image into meaningful regions, is a fundamental step in image processing, crucial for applications like computer vision, medical imaging, and object recognition. Image segmentation is an essential step of image processing that directly affects its success. Among the methods used for image segmentation, histogram-based thresholding is prevalent. Two well-known approaches to histogram-based thresholding are Otsu’s and Kapur’s methods in gray images that maximize the between-class variance and the entropy measure, respectively. Both techniques we ...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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