A new method of black-box fuzzy system identification optimized by genetic algorithm and its application to predict mixture thermal properties
International Journal of Numerical Methods for Heat & Fluid Flow
ISSN: 0961-5539
Article publication date: 3 October 2019
Issue publication date: 30 April 2020
Abstract
Purpose
This paper aims to present a black-box fuzzy system identification method coupled with genetic algorithm optimization approach to predict the mixture thermal conductivity at dissimilar temperatures and nanoparticle concentrations, in the examined domains.
Design/methodology/approach
WO3 nanoparticles are dispersed in the deionized water to produce a homogeneous mixture at various nanoparticles mass fractions of 0.1, 0.5, 1.0 and 5.0 Wt.%.
Findings
The results depicted that the models not only have satisfactory precision, but also have acceptable accuracy in dealing with non-trained input values.
Originality/value
The transmission electron microscopy is applied to measure the mean diameters, shape and morphology of the dry nanoparticles. Moreover, the stability of nanoparticles inside the water is evaluated by using zeta potential and dynamic light scattering (DLS) tests. Then, the prepared nanofluid thermal conductivity is presented at different values of temperatures and concentrations.
Keywords
Acknowledgements
The first author acknowledges the support provided by the National Key Research and Development Program of China under Grant 2016YFC0402103, National Natural Science Foundation of China under Grant 51709220.
Retraction notice: The publishers of International Journal of Numerical Methods for Heat & Fluid Flow wish to retract the article “A new method of black-box fuzzy system identification optimized by genetic algorithm and its application to predict mixture thermal properties” by W. He, S.A. Bagherzadeh, M. Tahmasebi, A. Abdollahi, M. Bahrami, R. Moradi, A. Karimipour, M. Goodarzi and Q-V Bach, which appeared in Volume 30, Issue 5, 2020.
It has come to our attention that there are concerns regarding the authorship of the paper and that the peer review process was compromised.
The authors of this paper would like to note that they do not agree with the content of this notice.
The International Journal of Numerical Methods for Heat & Fluid Flow submission guidelines make it clear that only those who have made a substantial contribution to the article should be credited as authors.
The publishers of the journal sincerely apologize to the readers.
Citation
He, W., Bagherzadeh, S.A., Tahmasebi, M., Abdollahi, A., Bahrami, M., Moradi, R., Karimipour, A., Goodarzi, M. and Bach, Q.-V. (2020), "A new method of black-box fuzzy system identification optimized by genetic algorithm and its application to predict mixture thermal properties", International Journal of Numerical Methods for Heat & Fluid Flow, Vol. 30 No. 5, pp. 2485-2499. https://doi.org/10.1108/HFF-12-2018-0758
Publisher
:Emerald Publishing Limited
Copyright © 2019, Emerald Publishing Limited