بدائل البحث:
driven optimization » design optimization (توسيع البحث), guided optimization (توسيع البحث), dose optimization (توسيع البحث)
models optimization » model optimization (توسيع البحث), process optimization (توسيع البحث), wolf optimization (توسيع البحث)
binary state » binary image (توسيع البحث), binary data (توسيع البحث)
state driven » data driven (توسيع البحث), wave driven (توسيع البحث), atp driven (توسيع البحث)
primary data » primary care (توسيع البحث)
driven optimization » design optimization (توسيع البحث), guided optimization (توسيع البحث), dose optimization (توسيع البحث)
models optimization » model optimization (توسيع البحث), process optimization (توسيع البحث), wolf optimization (توسيع البحث)
binary state » binary image (توسيع البحث), binary data (توسيع البحث)
state driven » data driven (توسيع البحث), wave driven (توسيع البحث), atp driven (توسيع البحث)
primary data » primary care (توسيع البحث)
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Business priorities.
منشور في 2025"…Based on a comprehensive assessment of service transmission reliability and time costs, a route satisfaction evaluation function model has been developed. Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …"
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85
Topology of 14-node communication network.
منشور في 2025"…Based on a comprehensive assessment of service transmission reliability and time costs, a route satisfaction evaluation function model has been developed. Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …"
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86
Routing policy based on path satisfaction.
منشور في 2025"…Based on a comprehensive assessment of service transmission reliability and time costs, a route satisfaction evaluation function model has been developed. Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …"
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87
Changes of risk value under different parameters.
منشور في 2025"…Based on a comprehensive assessment of service transmission reliability and time costs, a route satisfaction evaluation function model has been developed. Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …"
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88
Performance of active and standby paths.
منشور في 2025"…Based on a comprehensive assessment of service transmission reliability and time costs, a route satisfaction evaluation function model has been developed. Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …"
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89
Proposed model tuned hyperparameters.
منشور في 2024"…Next, we employ batch normalization to smooth and enhance the collected data, followed by feature extraction using the AlexNet model. …"
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90
Proposed model sensitivity outcome.
منشور في 2024"…Next, we employ batch normalization to smooth and enhance the collected data, followed by feature extraction using the AlexNet model. …"
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91
CNN-LSTM Model performance.
منشور في 2024"…Analytic approaches, both predictive and retrospective in nature, were used to interpret the data. Our primary objective was to determine the most effective model for predicting COVID-19 cases in the United Arab Emirates (UAE) and Malaysia. …"
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Proposed model specificity and DSC outcomes.
منشور في 2024"…Next, we employ batch normalization to smooth and enhance the collected data, followed by feature extraction using the AlexNet model. …"
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96
Bi-directional LSTM Model performance.
منشور في 2024"…Analytic approaches, both predictive and retrospective in nature, were used to interpret the data. Our primary objective was to determine the most effective model for predicting COVID-19 cases in the United Arab Emirates (UAE) and Malaysia. …"
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97
Prediction results of different models.
منشور في 2024"…In the hybrid model of this paper, the choice was made to use the Densenet architecture of CNN models with LightGBM as the primary model. …"
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98
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S1 Data -
منشور في 2025"…A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. …"
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100