بدائل البحث:
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), based optimization (توسيع البحث)
well optimization » wolf optimization (توسيع البحث), whale optimization (توسيع البحث), field optimization (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
based well » based cell (توسيع البحث), based web (توسيع البحث), based all (توسيع البحث)
binary a » binary _ (توسيع البحث), binary b (توسيع البحث), hilary a (توسيع البحث)
a model » _ model (توسيع البحث)
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), based optimization (توسيع البحث)
well optimization » wolf optimization (توسيع البحث), whale optimization (توسيع البحث), field optimization (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
based well » based cell (توسيع البحث), based web (توسيع البحث), based all (توسيع البحث)
binary a » binary _ (توسيع البحث), binary b (توسيع البحث), hilary a (توسيع البحث)
a model » _ model (توسيع البحث)
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81
Results of Decision tree.
منشور في 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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82
Results of Adaboost.
منشور في 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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83
Results of Random Forest.
منشور في 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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84
Before upsampling.
منشور في 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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85
Results of gradient boosting classifier.
منشور في 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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86
Results of Decision tree.
منشور في 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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87
Adaboost classifier results.
منشور في 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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88
Results of Lightbgm.
منشور في 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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89
Results of Lightbgm.
منشور في 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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90
Feature selection process.
منشور في 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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91
Results of KNN.
منشور في 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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92
After upsampling.
منشور في 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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93
Results of Extra tree.
منشور في 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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94
Gradient boosting classifier results.
منشور في 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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95
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96
The AD-PSO-Guided WOA LSTM framework.
منشور في 2025"…Out of all the models, LSTM produced the best results. The AD-PSO-Guided WOA algorithm was used to adjust the hyperparameters for the LSTM model. …"
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97
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98
Data_Sheet_1_A Global Optimizer for Nanoclusters.PDF
منشور في 2019"…This method is implemented in PyAR (https://github.com/anooplab/pyar) program. The global optimization in PyAR involves two parts, generation of several trial geometries and gradient-based local optimization of the trial geometries. …"
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99
Classification baseline performance.
منشور في 2025"…To overcome these limitations, this study introduces a comprehensive deep learning framework enhanced with the innovative bio-inspired Ocotillo Optimization Algorithm (OcOA), designed to improve the accuracy and efficiency of bone marrow cell classification. …"
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100
Feature selection results.
منشور في 2025"…To overcome these limitations, this study introduces a comprehensive deep learning framework enhanced with the innovative bio-inspired Ocotillo Optimization Algorithm (OcOA), designed to improve the accuracy and efficiency of bone marrow cell classification. …"