Search alternatives:
which optimization » weight optimization (Expand Search), whale optimization (Expand Search), policy optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
binary damage » binary image (Expand Search), binary data (Expand Search)
damage model » game model (Expand Search)
final model » animal model (Expand Search)
which optimization » weight optimization (Expand Search), whale optimization (Expand Search), policy optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
binary damage » binary image (Expand Search), binary data (Expand Search)
damage model » game model (Expand Search)
final model » animal model (Expand Search)
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1
Flow chart of INFO algorithm.
Published 2025“…By establishing the INFO-KELM optimization model, the final optimized structure is obtained. …”
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2
Algorithm for generating hyperparameter.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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3
Results of machine learning algorithm.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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4
ROC comparison of machine learning algorithm.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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5
Optimal scheduling model of microgrid based on improved dung beetle optimization algorithm
Published 2024“…<p>In view of the strong uncertainty and intermittency of distributed power sources in microgrids and the shortcomings of the traditional dung beetle optimizer (DBO) algorithm with slow convergence, poor robustness and ease of falling into a local optimum, an optimal scheduling model for microgrids based on the improved dung beetle optimization algorithm is proposed. …”
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6
Optimization results of different algorithms.
Published 2024“…Moreover, the multi-objective genetic algorithm optimized the structural block brake design. …”
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7
The ANFIS algorithm details.
Published 2025“…The existence of uncontrollable factors affects the decision-making process, which is a problem for investors who are responsible for the final financial decisions on how to allocate their budgets to financial assets in their investment portfolios. …”
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8
Optimized process of the random forest algorithm.
Published 2023“…Finally, the constructed random forest-based gas explosion early warning model is compared with a classification model based on the support vector machine (SVM) algorithm. …”
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9
Firefly optimization algorithm flowchart.
Published 2025“…And finally, an improved PSO-IFA hybrid optimization algorithm (PSO-IFAH) was proposed in the paper. …”
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10
Best optimizer results of Lightbgm.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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11
Best optimizer results of Adaboost.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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12
Best optimizer results of Lightbgm.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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13
Random forest with hyperparameter optimization.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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14
Best optimizer results of KNN.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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15
Best optimizer results of KNN.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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16
The flowchart of Algorithm 2.
Published 2024“…For the former, it is further divided into two sub-problems according to the stochastic nature of passenger no-show behavior, which is optimized iteratively. Finally, the effectiveness of the proposed model and algorithm is evaluated through numerical studies. …”
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17
Ensemble model architecture.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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18
Comparison table of the proposed model.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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19
Confusion matrix of ensemble model.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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20
Best optimizer results of Decision tree.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”