بدائل البحث:
robust optimization » process optimization (توسيع البحث), robust estimation (توسيع البحث), joint optimization (توسيع البحث)
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), based optimization (توسيع البحث)
primary data » primary care (توسيع البحث)
binary basic » binary mask (توسيع البحث)
basic model » based model (توسيع البحث), base model (توسيع البحث)
robust optimization » process optimization (توسيع البحث), robust estimation (توسيع البحث), joint optimization (توسيع البحث)
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), based optimization (توسيع البحث)
primary data » primary care (توسيع البحث)
binary basic » binary mask (توسيع البحث)
basic model » based model (توسيع البحث), base model (توسيع البحث)
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Pseudocode of artificial dragonfly algorithm.
منشور في 2023"…The primary objective is to investigate the effectiveness and robustness of the ADA algorithm in expediting the training phase of the HNN to attain an optimized EB<i>k</i>SAT logic representation. …"
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The Hopfield artificial neural network algorithm.
منشور في 2023"…The primary objective is to investigate the effectiveness and robustness of the ADA algorithm in expediting the training phase of the HNN to attain an optimized EB<i>k</i>SAT logic representation. …"
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Robustness Analysis of each model.
منشور في 2025"…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …"
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Flow diagram of Wan Abdullah method for HNN.
منشور في 2023"…The primary objective is to investigate the effectiveness and robustness of the ADA algorithm in expediting the training phase of the HNN to attain an optimized EB<i>k</i>SAT logic representation. …"
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Training error and accuracy for all HNN models.
منشور في 2023"…The primary objective is to investigate the effectiveness and robustness of the ADA algorithm in expediting the training phase of the HNN to attain an optimized EB<i>k</i>SAT logic representation. …"
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G<i>m</i>R performance of various HNN-EB<i>k</i>SAT models.
منشور في 2023"…The primary objective is to investigate the effectiveness and robustness of the ADA algorithm in expediting the training phase of the HNN to attain an optimized EB<i>k</i>SAT logic representation. …"
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<i>MAPE performance of various</i> HNN-EB<i>k</i>SAT models.
منشور في 2023"…The primary objective is to investigate the effectiveness and robustness of the ADA algorithm in expediting the training phase of the HNN to attain an optimized EB<i>k</i>SAT logic representation. …"
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RMSE performance of various HNN-EB<i>k</i>SAT models.
منشور في 2023"…The primary objective is to investigate the effectiveness and robustness of the ADA algorithm in expediting the training phase of the HNN to attain an optimized EB<i>k</i>SAT logic representation. …"
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MLP vs classification algorithms.
منشور في 2024"…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …"
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S1 Data -
منشور في 2023"…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …"
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Curve of step response signal of 6 algorithms.
منشور في 2023"…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …"
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Wilcoxon’s rank sum test results.
منشور في 2023"…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …"
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Flowchart of MSHHOTSA.
منشور في 2023"…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …"