COVID-19 X-ray image segmentation by modified whale optimization algorithm with population reduction

Chakraborty, Subhankari Prasad; Saha, Apu Kumar; Nama, Sukanta; Debnath, Sudhan

doi:10.1016/j.compbiomed.2021.104984

Cited by 81 publications

(42 citation statements)

References 49 publications

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“…WOA consists of three phases: encircling the prey, bubble-net attacking, and searching for the prey. WOA has been used to solve a wide range of optimization problems in different applications including feature selection [28], software defect prediction [29], clustering [30,31], classification [32,33], disease diagnosis [34], image segmentation [35,36], scheduling [37], forecasting [38,39], parameter estimation [40], global optimization [41], and photovoltaic energy generation systems [42,43]. Even though WOA is employed to tackle a wide variety of optimization problems, it still has flaws such as premature convergence, the imbalance between exploration and exploitation, and local optima stagnation [44,45].…”

Section: Introductionmentioning

confidence: 99%

EWOA-OPF: Effective Whale Optimization Algorithm to Solve Optimal Power Flow Problem

et al. 2021

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The optimal power flow (OPF) is a vital tool for optimizing the control parameters of a power system by considering the desired objective functions subject to system constraints. Metaheuristic algorithms have been proven to be well-suited for solving complex optimization problems. The whale optimization algorithm (WOA) is one of the well-regarded metaheuristics that is widely used to solve different optimization problems. Despite the use of WOA in different fields of application as OPF, its effectiveness is decreased as the dimension size of the test system is increased. Therefore, in this paper, an effective whale optimization algorithm for solving optimal power flow problems (EWOA-OPF) is proposed. The main goal of this enhancement is to improve the exploration ability and maintain a proper balance between the exploration and exploitation of the canonical WOA. In the proposed algorithm, the movement strategy of whales is enhanced by introducing two new movement strategies: (1) encircling the prey using Levy motion and (2) searching for prey using Brownian motion that cooperate with canonical bubble-net attacking. To validate the proposed EWOA-OPF algorithm, a comparison among six well-known optimization algorithms is established to solve the OPF problem. All algorithms are used to optimize single- and multi-objective functions of the OPF under the system constraints. Standard IEEE 6-bus, IEEE 14-bus, IEEE 30-bus, and IEEE 118-bus test systems are used to evaluate the proposed EWOA-OPF and comparative algorithms for solving the OPF problem in diverse power system scale sizes. The comparison of results proves that the EWOA-OPF is able to solve single- and multi-objective OPF problems with better solutions than other comparative algorithms.

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Section: Introductionmentioning

confidence: 99%

EWOA-OPF: Effective Whale Optimization Algorithm to Solve Optimal Power Flow Problem

et al. 2021

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“…Image segmentation problem with multilevel thresholding approach was solved using the new algorithm. Chakraborty et al [32] modified the Whale Optimization Algorithm (WOA) and segmented the COVID-19 X-ray images to diagnose the disease easily. Though all the CEC-winning algorithms are highly efficient in solving optimization problems, comparing performance among these efficient algorithms can be an attractive effort.…”

Section: Few Work On Verification Of Performance and Real-world Probl...mentioning

confidence: 99%

Comparative Performance Analysis of Differential Evolution Variants on Engineering Design Problems

et al. 2022

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Because of their superior problem-solving ability, nature-inspired optimization algorithms are being regularly used in solving complex real-world optimization problems. Engineering academics have recently focused on meta-heuristic algorithms to solve various optimization challenges. Among the state-of-the-art algorithms, Differential Evolution (DE) is one of the most successful algorithms and is frequently used to solve various industrial problems. Over the previous 2 decades, DE has been heavily modified to improve its capabilities. Several DE variations secured positions in IEEE CEC competitions, establishing their efficacy. However, to our knowledge, there has never been a comparison of performance across various CEC-winning DE versions, which could aid in determining which is the most successful. In this study, the performance of DE and its eight other IEEE CEC competition-winning variants are compared. First, the algorithms have evaluated IEEE CEC 2019 and 2020 bound-constrained functions, and the performances have been compared. One unconstrained problem from IEEE CEC 2011 problem suite and five other constrained mechanical engineering design problems, out of which four issues have been taken from IEEE CEC 2020 non-convex constrained optimization suite, have been solved to compare the performances. Statistical analyses like Friedman's test and Wilcoxon's test are executed to verify the algorithm's ability statistically. Performance analysis exposes that none of the DE variants can solve all the problems efficiently. Performance of SHADE and ELSHADE-SPACMA are considerable among the methods used for comparison to solve such mechanical design problems.

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“…These techniques represent a non-invasive test that presents accurate results in a very short time. Some examples of these detectors involve the use of CNN models [ 64 ], new DL architectures [ 65 ] and DL with metaheuristic techniques [ 66 ].…”

Section: Introductionmentioning

confidence: 99%

An agent-based transmission model of COVID-19 for re-opening policy design

Rodríguez

Cuevas

Zaldívar

et al. 2022

Computers in Biology and Medicine

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COVID-19 X-ray image segmentation by modified whale optimization algorithm with population reduction

Cited by 81 publications

References 49 publications

EWOA-OPF: Effective Whale Optimization Algorithm to Solve Optimal Power Flow Problem

EWOA-OPF: Effective Whale Optimization Algorithm to Solve Optimal Power Flow Problem

Comparative Performance Analysis of Differential Evolution Variants on Engineering Design Problems

An agent-based transmission model of COVID-19 for re-opening policy design

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