An artificial intelligence approach for modeling and prediction of water diffusion inside a carbon nanotube

Samad Ahadian, Yoshiyuki Kawazoe

研究成果: Article査読

15 被引用数 (Scopus)

抄録

Modeling of water flow in carbon nanotubes is still a challenge for the classic models of fluid dynamics. In this investigation, an adaptive-network-based fuzzy inference system (ANFIS) is presented to solve this problem. The proposed ANFIS approach can construct an input-output mapping based on both human knowledge in the form of fuzzy if-then rules and stipulated input-output data pairs. Good performance of the designed ANFIS ensures its capability as a promising tool for modeling and prediction of fluid flow at nanoscale where the continuum models of fluid dynamics tend to break down.

本文言語English
ページ(範囲)1054-1058
ページ数5
ジャーナルNanoscale Research Letters
4
9
DOI
出版ステータスPublished - 2009
外部発表はい

ASJC Scopus subject areas

  • 材料科学(全般)
  • 凝縮系物理学

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