Advances in Engineering Software, Journal Year: 2021, Volume and Issue: 154, P. 102973 - 102973
Published: Feb. 23, 2021
Language: Английский
Computer Methods in Applied Mechanics and Engineering, Journal Year: 2023, Volume and Issue: 415, P. 116200 - 116200
Published: July 10, 2023
Language: Английский
Citations
80
Computers in Biology and Medicine, Journal Year: 2022, Volume and Issue: 152, P. 106404 - 106404
Published: Dec. 6, 2022
Language: Английский
Citations
76
Archives of Computational Methods in Engineering, Journal Year: 2022, Volume and Issue: 29(7), P. 5579 - 5603
Published: July 4, 2022
Language: Английский
Citations
74
Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 169, P. 107922 - 107922
Published: Jan. 4, 2024
Language: Английский
Citations
28
IEEE Access, Journal Year: 2020, Volume and Issue: 8, P. 125306 - 125330
Published: Jan. 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.
Language: Английский
Citations
126
Neural Computing and Applications, Journal Year: 2021, Volume and Issue: 33(24), P. 16899 - 16919
Published: July 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.
Language: Английский
Citations
100
IEEE Access, Journal Year: 2021, Volume and Issue: 9, P. 56066 - 56092
Published: Jan. 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.
Language: Английский
Citations
90
Computers in Biology and Medicine, Journal Year: 2021, Volume and Issue: 136, P. 104609 - 104609
Published: July 3, 2021
Language: Английский
Citations
88
Computer Methods and Programs in Biomedicine, Journal Year: 2021, Volume and Issue: 201, P. 105949 - 105949
Published: Jan. 27, 2021
Language: Английский
Citations
79
Energy Reports, Journal Year: 2021, Volume and Issue: 7, P. 3979 - 3997
Published: July 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
Language: Английский
Citations
70