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Opposition-based Whale Optimization Algorithm
Published 2018“…The Whale Optimization Algorithm (WOA) is a newly proposed metaheuristic optimization algorithm, which simulate humpback whales hunting behavior. …”
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Binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem
Published 2023“…The new Binary Whale Optimization Algorithm is integrated with wrapper feature selection and validated on descriptor selection problem to improve Amphetamine-type stimulants drug classification result. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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A novel nonlinear time‑varying sigmoid transfer function in binary whale optimization algorithm for descriptors selection in drug classifcation
Published 2022“…In computational chemistry, the high-dimensional molecular descriptors contribute to the curse of dimensionality issue. Binary whale optimization algorithm (BWOA) is a recently proposed metaheuristic optimization algorithm that has been efficiently applied in feature selection. …”
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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
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Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors
Published 2025“…One of the powerful optimization algorithms that is used for feature selection is the Whale Optimization Algorithm (WOA), which is a nature-inspired metaheuristic optimization algorithm that mimics the social behavior of humpback whales. …”
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Q-learning whale optimization algorithm for test suite generation with constraints support
Published 2023“…This paper introduces a new variant of a metaheuristic algorithm based on the whale optimization algorithm (WOA), the Q-learning algorithm and the Exponential Monte Carlo Acceptance Probability called (QWOA-EMC). …”
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Selective harmonic elimination pulse width modulation for three-phase nine-level inverter using improved whale optimization algorithm
Published 2023“…Whale Optimization Algorithm (WOA) is one of the algorithms developed which capable of solving the non-linear equation and obtained suitable results for MLI. …”
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Improving amphetamine-type stimulants drug classification using chaotic-based time-varying binary whale optimization algorithm
Published 2022“…A new chaotic time-varying binary whale optimization algorithm (CBWOATV) is introduced in this paper to optimize the feature selection process in Amphetamine-type Stimulants (ATS) and non-ATS drugs classification. …”
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Combinatorial test suites generation strategy utilizing the whale optimization algorithm
Published 2020“…The experimental results of the test-suite generation indicate that WOA produces competitive outcomes compared to some selected single-based and population-based metaheuristic algorithms.…”
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Improved Ozone Level Detection through Feature Selection with Modified Whale Optimization Algorithm
Published 2024“…This study presents a new approach for ozone level detection through feature selection by the modified Whale Optimization Algorithm (mWOA). …”
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Improved Ozone Level Detection through Feature Selection with Modified Whale Optimization Algorithm
Published 2024“…This study presents a new approach for ozone level detection through feature selection by the modified Whale Optimization Algorithm (mWOA). …”
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Optimal power flow with renewable power generations using hyper-heuristic technique
Published 2024“…The solution employs a high-level hyper-heuristic technique called Exponential Monte Carlo with counter (EMCQ) to solve the problem of loss minimization. The technique selects and integrates the strengths of three low-level meta-heuristics algorithms, including Grey Wolf Optimizer (GWO), Barnacles Mating Optimizer (BMO), and Whale Optimization Algorithm (WOA), to achieve the best possible results. …”
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Hybrid binary whale with harris hawks for feature selection
Published 2022“…This study introduces the BWOAHHO memetic technique, which combines the binary hybrid Whale Optimization Algorithm (WOA) with Harris Hawks Optimization (HHO). …”
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Input-output based relation combinatorial testing using whale optimization algorithm for generating near optimum number of test suite
Published 2025“…This study proposes a combinatorial testing method utilizing the Whale Optimization Algorithm (WOA). The study compares the performance of WOA with various existing strategies, such as Greedy, Density, TVG, Union, ParaOrder, ReqOrder, ITTDG, AURA, Java Algorithm (CTJ), TTSGA, and AFA. …”
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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio...
Published 2023“…Comparing this developed algorithm with other algorithms shows its superiority in multi-objective optimization (MOO) evaluation metrics. …”
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Optimal power flow solutions for power system operations using moth-flame optimization algorithm
Published 2021“…In IEEE 57-bus test system, MFO offers a minimization of 19.16% compared to 19.03% and 18.98% for Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA) respectively. …”
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Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…The model employs a two-level structure, where the first level uses standard soft constraints as the objective function to evaluate solution quality, while the second level dynamically adapts to faculty-specific preferences. A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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