Majid Abdollahzade
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Management Science and Operations Research top 5%
- Control and Systems Engineering top 10%
- Economics and Econometrics
- Co-authors
- Arash MiranianSeyed Hossein IranmaneshHossein HassaniBehnam VahdaniSeyed Meysam MousaviReza KazemiMajid GhassemiM. J. Mahjoob
- Topics
- Energy Load and Power Forecasting (9 papers)Neural Networks and Applications (7 papers)Fuzzy Logic and Control Systems (5 papers)
- Cited by
- Management Science and Operations ResearchArtificial IntelligenceControl and Systems Engineering
- Partner nations
- IranUnited StatesUnited Kingdom
In The Last Decade
Majid Abdollahzade
24 papers receiving 469 citations
Peers
Comparison fields: 5 of 83
- Artificial Intelligence 151
- Electrical and Electronic Engineering 148
- Management Science and Operations Research 126
- Control and Systems Engineering 83
- Economics and Econometrics 42
Countries citing papers authored by Majid Abdollahzade
This map shows the geographic impact of Majid Abdollahzade's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Majid Abdollahzade with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Majid Abdollahzade more than expected).
Fields of papers citing papers by Majid Abdollahzade
This network shows the impact of papers produced by Majid Abdollahzade. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Majid Abdollahzade. The network helps show where Majid Abdollahzade may publish in the future.
Co-authorship network of co-authors of Majid Abdollahzade
This figure shows the co-authorship network connecting the top 25 collaborators of Majid Abdollahzade. A scholar is included among the top collaborators of Majid Abdollahzade based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Majid Abdollahzade. Majid Abdollahzade is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 0 | |
| 3 | 6 | |
| 4 | 8 | |
| 5 | 6 | |
| 6 | 14 | |
| 7 | 3 | |
| 8 | 3 | |
| 9 | 70 | |
| 10 | 10 | |
| 11 | 2 | |
| 12 | 43 | |
| 13 | 1 | |
| 14 | 7 | |
| 15 | 128 | |
| 16 | 67 | |
| 17 | 6 | |
| 18 | 36 | |
| 19 | 18 | |
| 20 | Chaotic time series forecasting using locally quadratic fuzzy neural models | 2 |
About Majid Abdollahzade
Majid Abdollahzade is a scholar working on Management Science and Operations Research, Control and Systems Engineering and Transportation, having authored 25 papers that have together received 485 indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (9 papers), Neural Networks and Applications (7 papers) and Fuzzy Logic and Control Systems (5 papers). The work is most often cited by research in Management Science and Operations Research (126 citations), Artificial Intelligence (151 citations) and Control and Systems Engineering (83 citations). Majid Abdollahzade has collaborated with scholars based in Iran, United States and United Kingdom. Frequent co-authors include Arash Miranian, Seyed Hossein Iranmanesh, Hossein Hassani, Behnam Vahdani, Seyed Meysam Mousavi, Reza Kazemi, Majid Ghassemi, M. J. Mahjoob, Goodarz Ahmadi and Ahmad Kalhor. Their work appears in journals such as IEEE Access, Information Sciences and IEEE Transactions on Neural Networks and Learning Systems.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.