An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion Inside a Carbon Nanotube
<p>Abstract</p> <p>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...
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Online Access: | http://dx.doi.org/10.1007/s11671-009-9361-3 |
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doaj-6efe26bbf20c4264988065a62b22c3b62020-11-24T21:19:54ZengSpringerOpenNanoscale Research Letters1931-75731556-276X2009-01-014910541058An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion Inside a Carbon NanotubeAhadian SamadKawazoe Yoshiyuki<p>Abstract</p> <p>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.</p> http://dx.doi.org/10.1007/s11671-009-9361-3Carbon nanotubeWater diffusionArtificial intelligenceModeling and prediction |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ahadian Samad Kawazoe Yoshiyuki |
spellingShingle |
Ahadian Samad Kawazoe Yoshiyuki An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion Inside a Carbon Nanotube Nanoscale Research Letters Carbon nanotube Water diffusion Artificial intelligence Modeling and prediction |
author_facet |
Ahadian Samad Kawazoe Yoshiyuki |
author_sort |
Ahadian Samad |
title |
An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion Inside a Carbon Nanotube |
title_short |
An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion Inside a Carbon Nanotube |
title_full |
An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion Inside a Carbon Nanotube |
title_fullStr |
An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion Inside a Carbon Nanotube |
title_full_unstemmed |
An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion Inside a Carbon Nanotube |
title_sort |
artificial intelligence approach for modeling and prediction of water diffusion inside a carbon nanotube |
publisher |
SpringerOpen |
series |
Nanoscale Research Letters |
issn |
1931-7573 1556-276X |
publishDate |
2009-01-01 |
description |
<p>Abstract</p> <p>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.</p> |
topic |
Carbon nanotube Water diffusion Artificial intelligence Modeling and prediction |
url |
http://dx.doi.org/10.1007/s11671-009-9361-3 |
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