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optimisation algorithm » optimization algorithms (Expand Search), maximization algorithm (Expand Search), identification algorithm (Expand Search)
process optimisation » process optimization (Expand Search), robust optimisation (Expand Search), process simulation (Expand Search)
design optimization » bayesian optimization (Expand Search)
based process » based processes (Expand Search), based probes (Expand Search), based proteins (Expand Search)
primary data » primary care (Expand Search)
linac based » lines based (Expand Search)
optimisation algorithm » optimization algorithms (Expand Search), maximization algorithm (Expand Search), identification algorithm (Expand Search)
process optimisation » process optimization (Expand Search), robust optimisation (Expand Search), process simulation (Expand Search)
design optimization » bayesian optimization (Expand Search)
based process » based processes (Expand Search), based probes (Expand Search), based proteins (Expand Search)
primary data » primary care (Expand Search)
linac based » lines based (Expand Search)
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Speed reducer design problem.
Published 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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Pressure vessel design problem.
Published 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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Gear train design problem.
Published 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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Tension/compression spring design problem.
Published 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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Zimbabwe model outputs on actual and optimized 2016 spending and impact by intervention.
Published 2021Subjects: -
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024Subjects: -
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024Subjects: -
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024Subjects: -
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024Subjects: -
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024Subjects: -
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024Subjects: -
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024Subjects: -
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