Nano Archive

An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion Inside a Carbon Nanotube

Ahadian, Samad and Kawazoe, Yoshiyuki (2009) An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion Inside a Carbon Nanotube. Nanoscale Research Letters, 4 (9). pp. 1054-1058. ISSN 1931-7573 (Print) 1556-276X (Online)

[img]
Preview
PDF - Published Version
225Kb

Official URL: http://www.springerlink.com/content/l8378xw03752hm...

Abstract

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.

Item Type:Article
Uncontrolled Keywords:Carbon nanotube - Water diffusion - Artificial intelligence - Modeling and prediction
Subjects:Physical Science > Nanophysics
Physical Science > Nano objects
ID Code:6920
Deposited By:Lesley Tobin
Deposited On:27 Aug 2009 14:13
Last Modified:02 Nov 2009 11:09

Repository Staff Only: item control page