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Using ANFIS technique in prediction of reverse flow in a solar chimney
Journal
IOP Conference Series: Materials Science and Engineering
ISSN
1757-8981
1757-899X
Date Issued
2021
Author(s)
Minh-Thu T Huynh
Thinh N Doan
Y Q Nguyen
DOI
10.1088/1757-899X/1109/1/012036
Abstract
In solar chimney, in order to save resources in Computational Fluid Dynamics (CFD),
this study aims to combine Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict reverse
flow and investigate the ventilation performance. The inputs to the model are heat flux in the
range of 200-1000W/m2, gap of 0.04-0.25m and height of 1-1.4m, while outputs are penetration
depth and mass flow rate. The results of R2 and RMSE are reasonable for training and testing
data, hence the ANFIS model is validated.
this study aims to combine Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict reverse
flow and investigate the ventilation performance. The inputs to the model are heat flux in the
range of 200-1000W/m2, gap of 0.04-0.25m and height of 1-1.4m, while outputs are penetration
depth and mass flow rate. The results of R2 and RMSE are reasonable for training and testing
data, hence the ANFIS model is validated.
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