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bayesian optimization » based optimization (Expand Search)
models optimization » model optimization (Expand Search), process optimization (Expand Search), wolf optimization (Expand Search)
binary series » primary series (Expand Search), webinar series (Expand Search), binary relief (Expand Search)
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Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results
Published 2025“…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …”
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3
The Pseudo-Code of the IRBMO Algorithm.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …”
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4
IRBMO vs. meta-heuristic algorithms boxplot.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …”
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5
IRBMO vs. feature selection algorithm boxplot.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …”
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6
Pseudo Code of RBMO.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …”
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7
P-value on CEC-2017(Dim = 30).
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …”
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8
Memory storage behavior.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …”
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9
Elite search behavior.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …”
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10
Description of the datasets.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …”
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11
S and V shaped transfer functions.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …”
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12
S- and V-Type transfer function diagrams.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …”
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13
Collaborative hunting behavior.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …”
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14
Friedman average rank sum test results.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …”
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15
IRBMO vs. variant comparison adaptation data.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …”
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Table_1_iRNA5hmC: The First Predictor to Identify RNA 5-Hydroxymethylcytosine Modifications Using Machine Learning.docx
Published 2020“…Afterward, we utilized a two-stage feature space optimization strategy to improve the feature representation ability, and trained a predictive model using support vector machine (SVM). …”
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18
Data_Sheet_1_The impact of family urban integration on migrant worker mental health in China.docx
Published 2024“…The analysis discerns three distinct clusters denoting varying degrees of urban integration within these familial units, namely high-level, medium-level, and low-level urban integration. We applied binary logit regression models to analyze the influence of family urban integration on the mental health among migrant workers. …”