Institution
Islamic Azad University
Education•Tehran, Iran•
About: Islamic Azad University is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Population & Catalysis. The organization has 83635 authors who have published 113437 publications receiving 1275049 citations. The organization is also known as: Azad University.
Topics: Population, Catalysis, Adsorption, Fuzzy logic, Nonlinear system
Papers published on a yearly basis
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TL;DR: Numerical algorithms for solving fuzzy system of linear equations (FSLE) based on the iterative Jacobi and Gauss Sidel methods in detail are considered and there are followed by convergence theorems.
213 citations
TL;DR: Owing to its demonstrated properties such as 3D interconnected porous structure, lightweight, large specific surface area, superparamagnetic behavior at room temperature, excellent adsorbent efficiency (93% removal) and also its simple and eco-friendly synthesis process, MBCNF/GOPA could be considered a promising candidate for removing cationic dye pollutants from aqueous solution.
212 citations
TL;DR: In this article, the behavior of the nanofluid was investigated for three different nanoparticles in the water-base fluid, namely copper, alumina and titania, and it was shown that a dual solution exists for negative values of the unsteadiness parameter A and, as it increases, the skin friction Cfr grows but the heat transfer rate Nur takes a decreasing trend.
212 citations
TL;DR: In this article, the authors examined the relationship between green logistics operations and energy demand, economic growth and environmental sustainability need to make factors for relationship clearer in a panel data of 43 different countries around the globe.
212 citations
TL;DR: In this article, the thermal conductivity ratio of MgO-MWCNTs/EG hybrid nanofluids has been predicted by an optimal artificial neural network at solid volume fractions of 0.05, 0.1%, 0.15, 0 2, 0.2, 0 4, and 0.6% in the temperature range of 25-50°C.
Abstract: In this paper, the thermal conductivity ratio of MgO-MWCNTs/EG hybrid nanofluids has been predicted by an optimal artificial neural network at solid volume fractions of 0.05%, 0.1%, 0.15%, 0.2%, 0.4% and 0.6% in the temperature range of 25–50 °C. In this way, at the first, thirty six experimental data was presented to determine the thermal conductivity ratio of the hybrid nanofluid. Then, four optimal artificial neural networks with 6, 8, 10 and 12 neurons in hidden layer were designed to predict the thermal conductivity ratio of the nanofluid. The comparison between four optimal ANN results and experimental showed that the ANN with 12 neurons in hidden layer was the best model. Moreover, the results obtained from the best ANN indicated the maximum deviation margin of 0.8%.
212 citations
Authors
Showing all 83704 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Ajit Kumar Mohanty | 141 | 1124 | 93062 |
| Pierluigi Paolucci | 138 | 1965 | 105050 |
| Eric Conte | 132 | 1206 | 84593 |
| Patrizia Azzi | 132 | 1275 | 83686 |
| D. Del Re | 131 | 1406 | 87230 |
| Jean-Laurent Agram | 128 | 1221 | 84423 |
| Seyed Mohsen Etesami | 128 | 1101 | 76488 |
| Jean-Charles Fontaine | 128 | 1190 | 84011 |
| Roberta Arcidiacono | 128 | 1322 | 80917 |
| Tejinder Virdee | 128 | 1208 | 74372 |
| Frank Hartmann | 127 | 1116 | 81455 |
| Paolo Azzurri | 126 | 1058 | 81651 |
| Achim Stahl | 124 | 1248 | 111121 |
| Federica Primavera | 120 | 876 | 63895 |
| Riccardo Andrea Manzoni | 120 | 946 | 67897 |