Search alternatives:
process optimization » model optimization (Expand Search)
models optimization » model optimization (Expand Search), wolf optimization (Expand Search), codon optimization (Expand Search)
primary data » primary care (Expand Search)
process optimization » model optimization (Expand Search)
models optimization » model optimization (Expand Search), wolf optimization (Expand Search), codon optimization (Expand Search)
primary data » primary care (Expand Search)
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Features selected by optimization algorithms.
Published 2024“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
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Iteration curve of the optimization process.
Published 2025“…The load-bearing mechanism of the proposed steel platform was analyzed theoretically, and finite element analysis (FEA) was employed to evaluate the stresses and deflections of key members. A particle swarm optimization (PSO) algorithm was integrated with the FEA model to optimize the cross-sectional dimensions of the primary beams, secondary beams, and foundation boxes, achieving a balance between load-bearing capacity and cost efficiency. …”
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Models’ performance without optimization.
Published 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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RNN performance comparison with/out optimization.
Published 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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Hybrid feature selection algorithm of CSCO-ROA.
Published 2024“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
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Construction process of RF.
Published 2025“…Secondly, the Criteria Importance Through Intercriteria Correlation (CRITIC) weight method is employed to determine the importance of these risk indicators, thereby enhancing the model’s prediction ability and stability. Following this, the FCM clustering algorithm is utilized for pre-processing sample data to improve the efficiency and accuracy of data classification. …”
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Proposed CVAE model.
Published 2024“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
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Segmentation results of the proposed model.
Published 2024“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
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