Nanoscale slip length prediction with machine learning tools
Abstract This work incorporates machine learning (ML) techniques, such as multivariate regression, the multi-layer perceptron, and random forest to predict the slip length at the nanoscale. Data points are collected both from our simulation data and data from the literature, and comprise Molecular D...
Enregistré dans:
| Auteurs principaux: | , |
|---|---|
| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2021
|
| Sujets: | |
| Accès en ligne: | https://doaj.org/article/42a0d2d89ab94a18bd3f2b823ffb3de8 |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|