1 |
Abdulshahed, A.M., A.P. Longstaff, and S. Fletcher, The application of ANFIS prediction models for thermal error compensation on CNC machine tools. Applied Soft Computing, 2015. 27: p. 158-168.
DOI
|
2 |
Takagi, T. and M. Sugeno, Fuzzy identification of systems and its applications to modeling and control. IEEE transactions on systems, man, and cybernetics, 1985(1): p. 116-132.
|
3 |
Mohammed, H.A., et al., Convective heat transfer and fluid flow study over a step using nanofluids: A review. Renewable and Sustainable Energy Reviews, 2011. 15(6): p. 2921-2939.
DOI
|
4 |
Daungthongsuk, W. and S. Wongwises, A critical review of convective heat transfer of nanofluids. Renewable and Sustainable Energy Reviews, 2007. 11(5): p. 797-817.5.
DOI
|
5 |
Kefayati, G.H.R., et al., Lattice Boltzmann simulation of natural convection in an open enclosure subjugated to water/copper nanofluid. International Journal of Thermal Sciences, 2012. 52: p. 91-101.14.
DOI
|
6 |
Khodadadi, J.M. and S.F. Hosseinizadeh, Nanoparticle-enhanced phase change materials (NEPCM) with great potential for improved thermal energy storage. International Communications in Heat and Mass Transfer, 2007. 34(5): p. 534-543.
DOI
|
7 |
Delavar, M.A., M. Farhadi, and K. Sedighi, Numerical simulation of direct methanol fuel cells using lattice Boltzmann method. International Journal of Hydrogen Energy, 2010. 35(17): p. 9306-9317.
DOI
|
8 |
Haghshenas Fard, M., M.N. Esfahany, and M.R. Talaie, Numerical study of convective heat transfer of nanofluids in a circular tube two-phase model versus single-phase model. International Communications in Heat and Mass Transfer, 2010. 37(1): p. 91-97.
DOI
|
9 |
Mahmoud, M.A. and A.E. Ben-Nakhi, Neural networks analysis of free laminar convection heat transfer in a partitioned enclosure. Communications in Nonlinear Science and Numerical Simulation, 2007. 12(7): p. 1265-1276.
DOI
|
10 |
Varol, Y., et al., Analysis of adaptive-network-based fuzzy inference system (ANFIS) to estimate buoyancy-induced flow field in partially heated triangular enclosures. Expert Systems with Applications, 2008. 35(4): p. 1989-1997.
DOI
|
11 |
Ryoo, J., Z. Dragojlovic, and D.A. Kaminski, Control of convergence in a computational fluid dynamics simulation using ANFIS. IEEE Transactions on Fuzzy Systems, 2005. 13(1): p. 42-47.
DOI
|
12 |
Pourtousi, M., et al., Prediction of multiphase flow pattern inside a 3D bubble column reactor using a combination of CFD and ANFIS. RSC Advances, 2015. 5(104): p. 85652-85672.
DOI
|
13 |
Brinkmann H, C., The viscosity of Concentrated Suspensions and Solutions. J. Chem. Phys., 1952. 20: p. 571.
DOI
|
14 |
Zeinali, M., et al., Influence of piston and magnetic coils on the field-dependent damping performance of a mixed-mode magnetorheological damper. Smart Materials and Structures, 2016. 25(5): p. 055010.
DOI
|
15 |
Safdari, A., H. Dabir, and K.C. Kim, Cubic-Interpolated Pseudo-particle model to predict thermal behavior of a nanofluid. Computers & Fluids, 2018. 164: p. 102-113.
DOI
|