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Data from Prediction for Mechanical Properties of Lean Duplex Stainless Steel by Using Random Forest
Lean duplex stainless steel (LDSS), which is expected to apply to infrastructures, exhibits rounded shape of stress-strain curve. For this reason, a constitutive equation which is able to accurately e
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Shrinkage and Crack Data and Program
In this study, the concrete shrinkage and creep laboraty data is analyzed based on the regression by ma- chine learning, linear regression and the design empirical predictionin Japan. The random forec
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Fatigue Database of Additively Manufactured Alloys
Fatigue is a process of mechanical degradation that is usually assessed based on empirical rules and experimental data obtained from standardized tests. Fatigue data of engineering materials are commo
Figshare2023-06-01 更新20
Machine Learning-Assisted Crystal Engineering of a Zeolite
Source Date file is provided here, the relevant raw data from each figure or table (in the main manuscript and in the Supplementary Information) are represented by a single sheet in the Excel document
Figshare2023-06-01 更新70
Machine Learning Models for Predicting Polymer Solubility in Solvents across Concentrations and Temperatures
Artificial intelligence and machine learning have become essential tools in predicting material properties to aid in the accelerated design of new materials. Polymer solubility, critical for new formu
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