Expert Systems with Applications, Год журнала: 2021, Номер 185, С. 115499 - 115499
Опубликована: Июль 8, 2021
Язык: Английский
Computer Methods in Applied Mechanics and Engineering, Год журнала: 2023, Номер 415, С. 116200 - 116200
Опубликована: Июль 10, 2023
Язык: Английский
Процитировано
81
Archives of Computational Methods in Engineering, Год журнала: 2022, Номер 29(7), С. 5579 - 5603
Опубликована: Июль 4, 2022
Язык: Английский
Процитировано
79
Computers in Biology and Medicine, Год журнала: 2022, Номер 152, С. 106404 - 106404
Опубликована: Дек. 6, 2022
Язык: Английский
Процитировано
77
Computers in Biology and Medicine, Год журнала: 2024, Номер 169, С. 107922 - 107922
Опубликована: Янв. 4, 2024
Язык: Английский
Процитировано
29
IEEE Access, Год журнала: 2020, Номер 8, С. 125306 - 125330
Опубликована: Янв. 1, 2020
Medical imaging techniques play a critical role in diagnosing diseases and patient healthcare. They help treatment, diagnosis, early detection. Image segmentation is one of the most important steps processing medical images, it has been widely used many applications. Multi-level thresholding (MLT) considered as simplest effective image techniques. Traditional approaches apply histogram methods; however, these methods face some challenges. In recent years, swarm intelligence have leveraged MLT, which an NP-hard problem. One main drawbacks SI when searching for optimum solutions, may get stuck local optima. This because during run methods, they create random sequences among different operators. this study, we propose hybrid based approach that combines features two marine predators algorithm (MPA) moth-?ame optimization (MFO). The proposed called MPAMFO, which, MFO utilized search method MPA to avoid trapping at MPAMFO MLT segmentation, showed excellent performance all experiments. To test experiments were carried out. first segment ten natural gray-scale images. second experiment tested real-world application, such CT images COVID-19. Therefore, thirteen MPAMFO. Furthermore, extensive comparisons with several implemented examine quality Overall experimental results confirm efficient approved its superiority over other existing methods.
Язык: Английский
Процитировано
127
Neural Computing and Applications, Год журнала: 2021, Номер 33(24), С. 16899 - 16919
Опубликована: Июль 7, 2021
Coronavirus disease 2019 (COVID-19) is pervasive worldwide, posing a high risk to people's safety and health. Many algorithms were developed identify COVID-19. One way of identifying COVID-19 by computed tomography (CT) images. Some segmentation methods are proposed extract regions interest from CT images improve the classification. In this paper, an efficient version recent manta ray foraging optimization (MRFO) algorithm based on oppositionbased learning called MRFO-OBL algorithm. The original MRFO can stagnate in local optima requires further exploration with adequate exploitation. Thus, population variety search space, we applied Opposition-based (OBL) MRFO's initialization step. solve image problem using multilevel thresholding. evaluated Otsu's method over compared six meta-heuristic algorithms: sine-cosine algorithm, moth flame optimization, equilibrium whale slap swarm obtained useful accurate results quality, consistency, evaluation matrices, such as peak signal-to-noise ratio structural similarity index. Eventually, more robustness for than all other compared. experimental demonstrate that outperforms under used metrics.
Язык: Английский
Процитировано
103
IEEE Access, Год журнала: 2021, Номер 9, С. 56066 - 56092
Опубликована: Янв. 1, 2021
This study integrates a tunicate swarm algorithm (TSA) with local escaping operator (LEO) for overcoming the weaknesses of original TSA. The LEO strategy in TSA–LEO prevents searching deflation TSA and improves convergence rate search efficiency agents. proposed was verified on CEC'2017 test suite, its performance compared seven metaheuristic algorithms (MAs). comparisons revealed that significantly helps by improving quality solutions accelerating rate. further tested real-world problem, namely, segmentation based objective functions Otsu Kapur. A set well-known evaluation metrics used to validate TSA–LEO. TSA-LEO outperforms other MA terms fitness, peak signal-to-noise ratio, structural similarity, feature findings.
Язык: Английский
Процитировано
90
Computers in Biology and Medicine, Год журнала: 2021, Номер 136, С. 104609 - 104609
Опубликована: Июль 3, 2021
Язык: Английский
Процитировано
89
Computer Methods and Programs in Biomedicine, Год журнала: 2021, Номер 201, С. 105949 - 105949
Опубликована: Янв. 27, 2021
Язык: Английский
Процитировано
81
Energy Reports, Год журнала: 2021, Номер 7, С. 3979 - 3997
Опубликована: Июль 3, 2021
Deriving optimal photovoltaic (PV) models' parameters have tremendous significance in simulating, evaluating, and controlling the systems. Determining unknown of these PV models is a multimodal, nonlinear, complex optimization problem. Hence, developing robust model to achieve effectively essential. This paper proposes an enhanced metaphor-free gradient-based optimizer (EGBO) for extracting quickly, precisely, reliably. In EGBO, rank-based mechanism employed update its efficiently. Also, logistic map (LC) implemented better use local escaping operator (LEO) original GBO algorithm. The proposed EGBO optimally identifies various model, such as single diodes, double modules. relevant results indicate that compared with most advanced methods, algorithm competitive reliability, accuracy, convergence speed. Moreover, from experimental data drawn manufacturer's datasheet demonstrate developed approach can offer highly accurate solutions at irradiances temperatures. Consequently, achieved confirm novel be presented utility tool deriving parameters, it helpful modeling
Язык: Английский
Процитировано
72