![]() | Up a level |
This graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
Use the mouse wheel or scroll gestures to zoom into the graph.
You can click on the nodes and links to highlight them and move the nodes by dragging them.
Hold down the "Ctrl" key or the "⌘" key while clicking on the nodes to open the list of this person's publications.
A word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Ghazanfari, A., Hamzeh, M., Mokhtari, H., & Karimi, H. (2012). Active power management of multihybrid fuel cell/supercapacitor power conversion system in a medium voltage microgrid. IEEE Transactions on Smart Grid, 3(4), 1903-1910. External link
Hamzeh, M., Ghazanfari, A., Ashourloo, M., & Karimi, H. (2014, June). Oscillatory current management for DC microgrids with high penetration of single-phase AC loads [Paper]. 2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE 2014), Istanbul, Turkey. External link
Sherkatghanad, Z., Ghazanfari, A., & Makarenkov, V. (2024). A self-attention-based CNN-Bi-LSTM model for accurate state-of-charge estimation of lithium-ion batteries. Journal of Energy Storage, 88, 111524 (10 pages). External link
Zabetian-Hosseini, A., Ghazanfari, A., & Boulet, B. (2024). A finite-state machine-based control design for thermal and state-of-charge balancing of lithium iron phosphate battery using flyback converters. Battery Energy, 3(4), 20230055 (16 pages). Available