Akram Seifi

1.0k total citations
28 papers, 720 citations indexed

About

Akram Seifi is a scholar working on Environmental Engineering, Water Science and Technology and Ocean Engineering. According to data from OpenAlex, Akram Seifi has authored 28 papers receiving a total of 720 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Environmental Engineering, 10 papers in Water Science and Technology and 6 papers in Ocean Engineering. Recurrent topics in Akram Seifi's work include Hydrological Forecasting Using AI (15 papers), Hydrology and Watershed Management Studies (8 papers) and Water resources management and optimization (5 papers). Akram Seifi is often cited by papers focused on Hydrological Forecasting Using AI (15 papers), Hydrology and Watershed Management Studies (8 papers) and Water resources management and optimization (5 papers). Akram Seifi collaborates with scholars based in Iran, Hungary and United States. Akram Seifi's co-authors include Majid Dehghani, Hossien Riahi-Madvar, Mohammad Ehteram, Vijay P. Singh, Amir Mosavi, Vijay P. Singh, Ali Torabi Haghighi, Hossein Ghayoumi Zadeh, Bahram Gharabaghi and Ely Salwana and has published in prestigious journals such as The Science of The Total Environment, Journal of Hydrology and Energy Conversion and Management.

In The Last Decade

Akram Seifi

28 papers receiving 703 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Akram Seifi Iran 14 415 325 168 103 91 28 720
Adrienn Dineva Hungary 11 336 0.8× 257 0.8× 224 1.3× 101 1.0× 115 1.3× 19 834
Seyed Babak Haji Seyed Asadollah Iran 13 519 1.3× 482 1.5× 197 1.2× 72 0.7× 136 1.5× 31 928
Karamjit Bhatia India 14 372 0.9× 388 1.2× 241 1.4× 91 0.9× 59 0.6× 41 834
Fatemeh Barzegari Banadkooki Iran 11 356 0.9× 250 0.8× 163 1.0× 75 0.7× 53 0.6× 18 550
Elnaz Sharghi Iran 18 408 1.0× 333 1.0× 257 1.5× 89 0.9× 114 1.3× 29 760
Saman Maroufpoor Iran 15 319 0.8× 211 0.6× 211 1.3× 84 0.8× 92 1.0× 20 634
Vahid Karimi Iran 13 514 1.2× 317 1.0× 266 1.6× 102 1.0× 56 0.6× 21 808
Keyvan Asghari Iran 10 329 0.8× 272 0.8× 151 0.9× 56 0.5× 136 1.5× 24 581
A. A. Masrur Ahmed Australia 15 482 1.2× 334 1.0× 183 1.1× 116 1.1× 96 1.1× 36 863
Aman Mohammad Kalteh Iran 10 508 1.2× 413 1.3× 279 1.7× 154 1.5× 51 0.6× 13 901

Countries citing papers authored by Akram Seifi

Since Specialization
Citations

This map shows the geographic impact of Akram Seifi'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 Akram Seifi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Akram Seifi more than expected).

Fields of papers citing papers by Akram Seifi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Akram Seifi. 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 Akram Seifi. The network helps show where Akram Seifi may publish in the future.

Co-authorship network of co-authors of Akram Seifi

This figure shows the co-authorship network connecting the top 25 collaborators of Akram Seifi. A scholar is included among the top collaborators of Akram Seifi 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 Akram Seifi. Akram Seifi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Seifi, Akram, et al.. (2025). Uncertainty assessment based on data decomposition and Boruta-driven extreme gradient boosting to predict spatiotemporal urban air dust heavy metal index. Atmospheric Pollution Research. 16(11). 102654–102654. 1 indexed citations
2.
Pourebrahim, Sharareh, Akram Seifi, Mohammad Ehteram, Mehrdad Hadipour, & Jit Ern Chen. (2025). The CEEMDAN-EWT-CNN-GRU-SVM model: A robust framework for decomposing non-stationary time series, extracting data features, and predicting solar radiation. Results in Engineering. 25. 104267–104267. 3 indexed citations
3.
Seifi, Akram, et al.. (2024). A robust multi-model framework for groundwater level prediction: The BFSA-MVMD-GRU-RVM model. Results in Engineering. 24. 103250–103250. 9 indexed citations
4.
Molaei, Mehdi, et al.. (2024). Treatment of Wastewater from Methylene Blue Dye and E. Coli Bacteria by High-Performance Fe3O4/rGO/TiO2 Nanocatalyst. Journal of Fluorescence. 35(8). 7099–7108. 4 indexed citations
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Elbeltagi, Ahmed, Akram Seifi, Mohammad Ehteram, et al.. (2023). GLUE analysis of meteorological-based crop coefficient predictions to derive the explicit equation. Neural Computing and Applications. 35(20). 14799–14824. 11 indexed citations
7.
Ehteram, Mohammad, Akram Seifi, & Fatemeh Barzegari Banadkooki. (2023). Application of Machine Learning Models in Agricultural and Meteorological Sciences. 6 indexed citations
8.
Zadeh, Hossein Ghayoumi, et al.. (2023). Predicting Hydropower Production Using Deep Learning CNN-ANN Hybridized with Gaussian Process Regression and Salp Algorithm. Water Resources Management. 37(9). 3671–3697. 10 indexed citations
9.
Ehteram, Mohammad, et al.. (2022). Uncertainty and spatial analysis in wheat yield prediction based on robust inclusive multiple models. Environmental Science and Pollution Research. 30(8). 20887–20906. 6 indexed citations
10.
Seifi, Akram, et al.. (2022). Multi-model ensemble prediction of pan evaporation based on the Copula Bayesian Model Averaging approach. Engineering Applications of Artificial Intelligence. 114. 105124–105124. 28 indexed citations
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Seifi, Akram, et al.. (2020). Irrigation Water Use Efficiency and Yield of Pistachio under Aerated Subsurface Drip Irrigation System. Journal of Agricultural Science and Technology. 22(6). 1655–1670. 2 indexed citations
14.
Zadeh, Hossein Ghayoumi, et al.. (2020). A novel equation for longitudinal dispersion coefficient prediction based on the hybrid of SSMD and whale optimization algorithm. The Science of The Total Environment. 716. 137007–137007. 26 indexed citations
15.
Seifi, Akram, et al.. (2020). Pan evaporation estimation and derivation of explicit optimized equations by novel hybrid meta-heuristic ANN based methods in different climates of Iran. Computers and Electronics in Agriculture. 173. 105418–105418. 46 indexed citations
16.
Seifi, Akram, Majid Dehghani, & Vijay P. Singh. (2020). Uncertainty analysis of water quality index (WQI) for groundwater quality evaluation: Application of Monte-Carlo method for weight allocation. Ecological Indicators. 117. 106653–106653. 103 indexed citations
17.
Riahi-Madvar, Hossien, Majid Dehghani, Akram Seifi, & Vijay P. Singh. (2019). Pareto Optimal Multigene Genetic Programming for Prediction of Longitudinal Dispersion Coefficient. Water Resources Management. 33(3). 905–921. 27 indexed citations
18.
Dehghani, Majid, Akram Seifi, & Hossien Riahi-Madvar. (2019). Novel forecasting models for immediate-short-term to long-term influent flow prediction by combining ANFIS and grey wolf optimization. Journal of Hydrology. 576. 698–725. 75 indexed citations
19.
Seifi, Akram & Hossien Riahi-Madvar. (2018). Improving one-dimensional pollution dispersion modeling in rivers using ANFIS and ANN-based GA optimized models. Environmental Science and Pollution Research. 26(1). 867–885. 33 indexed citations
20.

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.

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