NNI‐SMOTE‐XGBoost: A Novel Small Sample Analysis Method for Properties Prediction of Polymer Materials-Reference-Cited by-同舟云学术

NNI‐SMOTE‐XGBoost: A Novel Small Sample Analysis Method for Properties Prediction of Polymer Materials

Published:2021-05-02 Issue:5 Volume:30 Page:2100010
ISSN:1022-1344
Container-title:Macromolecular Theory and Simulations
language:en
Short-container-title:Macro Theory & Simulations

Author:

Li Dazi¹^ORCID,Liu Jianxun¹,Liu Jun²

Affiliation:

1. College of Information Science and Technology Beijing University of Chemical Technology Beijing 100029 China

2. Key Laboratory of Beijing City on Preparation and Processing of Novel Polymer Materials Beijing University of Chemical Technology Beijing 100029 China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Materials Chemistry,Inorganic Chemistry,Polymers and Plastics,Organic Chemistry,Condensed Matter Physics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mats.202100010

Reference30 articles.

1. COMPUTATIONAL SIMULATION OF ELASTOMER NANOCOMPOSITES: CURRENT PROGRESS AND FUTURE CHALLENGES

2. Improved crack growth resistance and its molecular origin of natural rubber/carbon black by nanodispersed clay

3. Preparation of nano-zinc oxide/EPDM composites with both good thermal conductivity and mechanical properties

4. Machine learning in materials genome initiative: A review

5. Machine Learning Approach for Prediction and Understanding of Glass-Forming Ability

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