Elham Fijani

22 papers receiving 1.1k citations

Peers

Elham Fijani
Comparison fields: 5 of 80
  • Environmental Engineering 724
  • Water Science and Technology 538
  • Geochemistry and Petrology 392
  • Artificial Intelligence 170
  • Global and Planetary Change 166
Replace Mohammad Nakhaei with:
Mohammad Nakhaei Iran
Yunjung Hyun South Korea
Shiyang Yin China
Evangelos Tziritis Greece
Kishan Singh Rawat India
Rachida Bouhlila Tunisia
Srinivas Pasupuleti India
Abhay M. Varade India
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Elham Fijani relative to Mohammad Nakhaei Iran Mohammad Nakhaei's profile →
Citations per field
00.5×2.6×
Mohammad Nakhaei · 1×
Citations per year

Countries citing papers authored by Elham Fijani

Since Specialization
Citations

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

Fields of papers citing papers by Elham Fijani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Elham Fijani

This figure shows the co-authorship network connecting the top 25 collaborators of Elham Fijani. A scholar is included among the top collaborators of Elham Fijani 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 Elham Fijani. Elham Fijani 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
#WorkIndexed citations
1 0
2 0
3 15
4 16
5 4
6 58
7
Evaluation of Effective Processes on Groundwater Quality of Meshgin-Shahr Plain by Integration of Geochemical and Statistical Methods
1
8 147
9 161
10 174
11 83
12 45
13 88
14 1
15 1
16
Optimization of DRASTIC method by supervised committee machine artificial intelligence for groundwater vulnerability assessment in Maragheh-Bonab plain aquifer, Iran.
0
17
Hierarchical Bayesian Model Averaging for Non-Uniqueness and Uncertainty Analysis of Artificial Neural Networks
1
18 14
19
SPATIAL PREDICTION OF FLUORIDE CONCENTRATION USING ARTIFICIAL NEURAL NETWORKS AND GEOSTATIC MODELS
5
20 4

About Elham Fijani

Elham Fijani is a scholar working on Geochemistry and Petrology, Environmental Engineering and Water Science and Technology, having authored 25 papers that have together received 1.2k indexed citations. Recurring topics across this work include Groundwater and Isotope Geochemistry (12 papers), Hydrological Forecasting Using AI (6 papers) and Groundwater and Watershed Analysis (5 papers). The work is most often cited by research in Geochemistry and Petrology (392 citations), Environmental Engineering (724 citations) and Water Science and Technology (538 citations). Elham Fijani has collaborated with scholars based in Iran, United States and Canada. Frequent co-authors include Asghar Asghari Moghaddam, Rahim Barzegar, Evangelos Tziritis, Ravinesh C. Deo, Frank T.‐C. Tsai, Ata Allah Nadiri, Jan Adamowski, Konstantinos Skordas, Barnali Dixon and Gökmen Tayfur. Their work appears in journals such as The Science of The Total Environment, Journal of Hydrology and Environmental Science and Pollution Research.

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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