Search alternatives:
function optimization » reaction optimization (Expand Search), formulation optimization (Expand Search), generation optimization (Expand Search)
process optimization » model optimization (Expand Search)
basis function » loss function (Expand Search), brain function (Expand Search), barrier function (Expand Search)
binary basis » binary mask (Expand Search), binary pairs (Expand Search)
can process » a process (Expand Search), carlo process (Expand Search), apar process (Expand Search)
function optimization » reaction optimization (Expand Search), formulation optimization (Expand Search), generation optimization (Expand Search)
process optimization » model optimization (Expand Search)
basis function » loss function (Expand Search), brain function (Expand Search), barrier function (Expand Search)
binary basis » binary mask (Expand Search), binary pairs (Expand Search)
can process » a process (Expand Search), carlo process (Expand Search), apar process (Expand Search)
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Classification performance after optimization.
Published 2025“…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …”
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ANOVA test for optimization results.
Published 2025“…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …”
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Wilcoxon test results for optimization.
Published 2025“…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …”
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Wilcoxon test results for feature selection.
Published 2025“…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …”
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Feature selection metrics and their definitions.
Published 2025“…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …”
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Statistical summary of all models.
Published 2025“…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …”
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Feature selection results.
Published 2025“…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …”
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ANOVA test for feature selection.
Published 2025“…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …”
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Classification performance of ML and DL models.
Published 2025“…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …”
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Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm
Published 2025“…Improvements in sensitivity, specificity, and overall classification accuracy highlight the effectiveness of </p><p dir="ltr">combining deep learning with optimization techniques. Our results show that deep learning and optimization </p><p dir="ltr">methods, such as the binary GWO algorithm, can be successfully applied to melanoma diagnosis. …”
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Analysis and design of algorithms for the manufacturing process of integrated circuits
Published 2023“…<p>Abstract: The stage of transporting semiconductor chips from the wafer to the support strip is crucial in the integrated circuit manufacturing process. This process can be modeled as a combinatorial optimization problem where the objective is to reduce the total distance the robotic arm must travel to pick up each chip and place it in its corresponding position within the support structure. …”
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Table_1_bSRWPSO-FKNN: A boosted PSO with fuzzy K-nearest neighbor classifier for predicting atopic dermatitis disease.docx
Published 2023“…</p>Methods<p>This paper establishes a medical prediction model for the first time on the basis of the enhanced particle swarm optimization (SRWPSO) algorithm and the fuzzy K-nearest neighbor (FKNN), called bSRWPSO-FKNN, which is practiced on a dataset related to patients with AD. …”
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