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

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Author(s): Ahadian Samad | Kawazoe Yoshiyuki

Journal: Nanoscale Research Letters
ISSN 1931-7573

Volume: 4;
Issue: 9;
Start page: 1054;
Date: 2009;
Original page

Keywords: Carbon nanotube | Water diffusion | Artificial intelligence | Modeling and prediction

ABSTRACT
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.

Tango Jona
Tangokurs Rapperswil-Jona

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