بدائل البحث:
function optimization » reaction optimization (توسيع البحث), formulation optimization (توسيع البحث), generation optimization (توسيع البحث)
while optimization » whale optimization (توسيع البحث), wolf optimization (توسيع البحث), phase optimization (توسيع البحث)
basis function » loss function (توسيع البحث), brain function (توسيع البحث), barrier function (توسيع البحث)
binary basis » binary mask (توسيع البحث), binary pairs (توسيع البحث)
function optimization » reaction optimization (توسيع البحث), formulation optimization (توسيع البحث), generation optimization (توسيع البحث)
while optimization » whale optimization (توسيع البحث), wolf optimization (توسيع البحث), phase optimization (توسيع البحث)
basis function » loss function (توسيع البحث), brain function (توسيع البحث), barrier function (توسيع البحث)
binary basis » binary mask (توسيع البحث), binary pairs (توسيع البحث)
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MSE for ILSTM algorithm in binary classification.
منشور في 2023"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
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Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm
منشور في 2025"…This strategy </p><p dir="ltr">not only improves detection efficiency and accuracy but also supports early diagnosis and treatment planning, </p><p dir="ltr">leading to better patient outcomes. By leveraging the binary GWO algorithm to optimize the feature selection </p><p dir="ltr">process and CNNs for image classification, the proposed approach reduces computational costs while increasing </p><p dir="ltr">classification accuracy. …"
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The flowchart of the proposed algorithm.
منشور في 2024"…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …"
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Data_Sheet_1_A Global Optimizer for Nanoclusters.PDF
منشور في 2019"…<p>We have developed an algorithm to automatically build the global minimum and other low-energy minima of nanoclusters. …"
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Data_Sheet_1_Posiform planting: generating QUBO instances for benchmarking.pdf
منشور في 2023"…<p>We are interested in benchmarking both quantum annealing and classical algorithms for minimizing quadratic unconstrained binary optimization (QUBO) problems. …"
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Classification performance after optimization.
منشور في 2025"…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …"
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ANOVA test for optimization results.
منشور في 2025"…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …"
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Wilcoxon test results for optimization.
منشور في 2025"…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …"
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Datasets and their properties.
منشور في 2023"…In addition, we designed nested transfer (NT) functions and investigated the influence of the function on the level-1 optimizer. The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …"
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Parameter settings.
منشور في 2023"…In addition, we designed nested transfer (NT) functions and investigated the influence of the function on the level-1 optimizer. The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …"
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Flow diagram of the proposed model.
منشور في 2025"…<div><p>Machine learning models are increasingly applied to assisted reproductive technologies (ART), yet most studies rely on conventional algorithms with limited optimization. This proof-of-concept study investigates whether a hybrid Logistic Regression–Artificial Bee Colony (LR–ABC) framework can enhance predictive performance in in vitro fertilization (IVF) outcomes while producing interpretable, hypothesis-driven associations with nutritional and pharmaceutical supplement use. …"
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Wilcoxon test results for feature selection.
منشور في 2025"…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …"
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Feature selection metrics and their definitions.
منشور في 2025"…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …"
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Statistical summary of all models.
منشور في 2025"…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …"
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Feature selection results.
منشور في 2025"…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …"
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ANOVA test for feature selection.
منشور في 2025"…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …"