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A Novel Gaussian Process Surrogate Model with Expected Prediction Error for Optimization under Constraints
Optimization, particularly constrained optimization problems (COPs), is fundamental in engineering, influencing various sectors with its critical role in enhancing le maudit vape institut design efficiency, reducing experimental costs, and shortening testing cycles.This study explores the challenges inherent in COPs, with a focus on developing effi
Deformation Monitoring of Slopes With a Shipborne InSAR System: A Case Study of the Lancang River Gorge
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Mosquito Surveillance and Polymerase Chain Reaction Detection of West Nile Virus, New York State
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Utilizing Artificial Neural Networks and Random Forests to Forecast the Dynamic Amplification Factors of Non-Structural Components
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