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[HTML][HTML] A deep neural network for accurate and robust prediction of the glass transition temperature of polyhydroxyalkanoate homo-and copolymers

Z Jiang, J Hu, BL Marrone, G Pilania, X Yu - Materials, 2020 - mdpi.com
The purpose of this study was to develop a data-driven machine learning model to predict
the performance properties of polyhydroxyalkanoates (PHAs), a group of biosourced …
被引用次数：17 相关文章
[HTML] nih.gov

[HTML][HTML] A Deep Neural Network for Accurate and Robust Prediction of the Glass Transition Temperature of Polyhydroxyalkanoate Homo-and Copolymers

Z Jiang, J Hu, BL Marrone, G Pilania, XB Yu - Materials, 2020 - ncbi.nlm.nih.gov
The purpose of this study was to develop a data-driven machine learning model to predict
the performance properties of polyhydroxyalkanoates (PHAs), a group of biosourced …

A Deep Neural Network for Accurate and Robust Prediction of the Glass Transition Temperature of Polyhydroxyalkanoate Homo-and Copolymers

Z Jiang, J Hu, BL Marrone, G Pilania, XB Yu - search.proquest.com
The purpose of this study was to develop a data-driven machine learning model to predict
the performance properties of polyhydroxyalkanoates (PHAs), a group of biosourced …

A Deep Neural Network for Accurate and Robust Prediction of the Glass Transition Temperature of Polyhydroxyalkanoate Homo-and Copolymers.

Z Jiang, J Hu, BL Marrone, G Pilania… - Materials (1996 …, 2020 - search.ebscohost.com
The purpose of this study was to develop a data-driven machine learning model to predict
the performance properties of polyhydroxyalkanoates (PHAs), a group of biosourced …
[PDF] academia.edu

[PDF][PDF] A Deep Neural Network for Accurate and Robust Prediction of the Glass Transition Temperature of Polyhydroxyalkanoate Homo-and Copolymers

Z Jiang, J Hu, BL Marrone, G Pilania, XB Yu - academia.edu
The purpose of this study was to develop a data-driven machine learning model to predict
the performance properties of polyhydroxyalkanoates (PHAs), a group of biosourced …

A Deep Neural Network for Accurate and Robust Prediction of the Glass Transition Temperature of Polyhydroxyalkanoate Homo-and Copolymers.

Z Jiang, J Hu, BL Marrone, G Pilania… - Materials (Basel …, 2020 - europepmc.org
The purpose of this study was to develop a data-driven machine learning model to predict
the performance properties of polyhydroxyalkanoates (PHAs), a group of biosourced …

[引用][C] A Deep Neural Network for Accurate and Robust Prediction of the Glass Transition Temperature of Polyhydroxyalkanoate Homo-and Copolymers

Z Jiang, J Hu, BL Marrone, G Pilania, XB Yu - Materials, 2020 - ui.adsabs.harvard.edu
A Deep Neural Network for Accurate and Robust Prediction of the Glass Transition
Temperature of Polyhydroxyalkanoate Homo- and Copolymers - NASA/ADS Now on home …

A Deep Neural Network for Accurate and Robust Prediction of the Glass Transition Temperature of Polyhydroxyalkanoate Homo-and Copolymers

Z Jiang, J Hu, BL Marrone, G Pilania, XB Yu - Materials, 2020 - osti.gov
The purpose of this study was to develop a data-driven machine learning model to predict
the performance properties of polyhydroxyalkanoates (PHAs), a group of biosourced …

A deep neural network for accurate and robust prediction of the glass transition temperature of polyhydroxyalkanoate homo-and copolymers

Z Jiang, J Hu, BL Marrone, G Pilania, X Yu - Materials, 2020 - lanlexperts.elsevierpure.com
The purpose of this study was to develop a data-driven machine learning model to predict
the performance properties of polyhydroxyalkanoates (PHAs), a group of biosourced …

A Deep Neural Network for Accurate and Robust Prediction of the Glass Transition Temperature of Polyhydroxyalkanoate Homo-and Copolymers

Z Jiang, J Hu, BL Marrone… - Materials (Basel …, 2020 - pubmed.ncbi.nlm.nih.gov
The purpose of this study was to develop a data-driven machine learning model to predict
the performance properties of polyhydroxyalkanoates (PHAs), a group of biosourced …