Institution
Iran University of Science and Technology
Education•Tehran, Iran•
About: Iran University of Science and Technology is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Nonlinear system & Finite element method. The organization has 12917 authors who have published 24965 publications receiving 372013 citations. The organization is also known as: Governmental Technical Institute & Advanced Art College.
Papers published on a yearly basis
Papers
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TL;DR: Several deep convolutional networks with the introduced training techniques for classifying X-ray images into three classes: normal, pneumonia, and COVID-19 are trained, and a neural network that is a concatenation of Xception and ResNet50V2 networks is proposed that achieved the best accuracy.
290 citations
TL;DR: A novel chaos-based image encryption algorithm to encrypt color images by using a Coupled Two-dimensional Piecewise Nonlinear Chaotic Map, called CTPNCM, and a masking process that yields better security performance in comparison to the results obtained from other algorithms.
288 citations
TL;DR: In this article, a review of ultraviolet photodetectors (PDs) is presented, with a focus on the unique advantages of different UV PDs, current device schemes and demonstrations, novel structures and new material compounds which are used to fabrication of PDs.
288 citations
TL;DR: The honey-bee mating optimization (HBMO) algorithm is presented and tested with a nonlinear, continuous constrained problem with continuous decision and state variables to demonstrate the efficiency of the algorithm in handling the single reservoir operation optimization problems.
Abstract: In recent years, evolutionary and meta-heuristic algorithms have been extensively used as search and optimization tools in various problem domains, including science, commerce, and engineering. Ease of use, broad applicability, and global perspective may be considered as the primary reason for their success. The honey-bee mating process has been considered as a typical swarm-based approach to optimization, in which the search algorithm is inspired by the process of real honey-bee mating. In this paper, the honey-bee mating optimization (HBMO) algorithm is presented and tested with a nonlinear, continuous constrained problem with continuous decision and state variables to demonstrate the efficiency of the algorithm in handling the single reservoir operation optimization problems. It is shown that the performance of the model is quite comparable with the results of the well-developed traditional linear programming (LP) solvers such as LINGO 8.0. Results obtained are quite promising and compare well with the final results of the other approach.
287 citations
TL;DR: The proposed algorithm is used to find the settings of control variables such as generator voltages, tap positions of tap changing transformers and the amount of reactive compensation devices to optimize a certain object.
285 citations
Authors
Showing all 13049 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Peter Hall | 132 | 1640 | 85019 |
| Josep M. Guerrero | 110 | 1197 | 60890 |
| Rahman Saidur | 97 | 576 | 34409 |
| Victor C. M. Leung | 91 | 1585 | 40397 |
| Mehdi Dehghan | 83 | 875 | 29225 |
| Amir H. Gandomi | 67 | 375 | 22192 |
| Toraj Mohammadi | 64 | 394 | 14043 |
| Emil Björnson | 62 | 458 | 17954 |
| Amir A. Zadpoor | 61 | 294 | 11653 |
| Majid R. Ayatollahi | 60 | 373 | 10771 |
| Ali Kaveh | 58 | 753 | 16647 |
| David Andrew Barry | 57 | 462 | 13363 |
| Miguel A. Mariño | 53 | 291 | 8304 |
| Ali Saberi | 51 | 448 | 10959 |
| Ali Maleki | 51 | 376 | 8853 |