A memetic animal migration optimizer for multimodal optimization

Taymaz Akan

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

Makale 2021 Evolving Systems13 ( 1 ) , pp. 1 - 144 61 Görüntülenme Süresiz Ambargo

Erişime Açık

Brain magnetic resonance image (MRI) segmentation using multimodal optimization

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One of the highly focused areas in the medical science community is segmenting tumors from brain magnetic resonance imaging (MRI). The diagnosis of malignant tumors at an early stage is necessary to provide treatment for patients. The patient’s prognosis will improve if it is detected early. Medical experts use a manual method of segmentation when making a diagnosis of brain tumors. This study proposes a new approach to simplify and automate this process. In recent research, multi-level segmentation has been widely used in medical image analysis, and the effectiveness and precision of the segm ...Daha fazlası

Makale 2024 Multimedia Tools and Applications 2 Görüntülenme

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Multilevel image thresholding with multimodal optimization

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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

Makale 2021 Multimedia Tools and Applications80 ( 10 ) , pp. 1 - 15289 121 Görüntülenme Süresiz Ambargo

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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

Makale 2023 SOFT COMPUTING27 ( 23 ) , pp. 1 - 17922 22 Görüntülenme Süresiz Ambargo