Jazuli Abdullahi

799 total citations
22 papers, 612 citations indexed

About

Jazuli Abdullahi is a scholar working on Environmental Engineering, Artificial Intelligence and Global and Planetary Change. According to data from OpenAlex, Jazuli Abdullahi has authored 22 papers receiving a total of 612 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Environmental Engineering, 9 papers in Artificial Intelligence and 9 papers in Global and Planetary Change. Recurrent topics in Jazuli Abdullahi's work include Hydrological Forecasting Using AI (15 papers), Plant Water Relations and Carbon Dynamics (6 papers) and Water Quality Monitoring Technologies (5 papers). Jazuli Abdullahi is often cited by papers focused on Hydrological Forecasting Using AI (15 papers), Plant Water Relations and Carbon Dynamics (6 papers) and Water Quality Monitoring Technologies (5 papers). Jazuli Abdullahi collaborates with scholars based in Cyprus, Nigeria and Iran. Jazuli Abdullahi's co-authors include Gözen Elkiran, Vahid Nourani, Sani I. Abba, Sinan Jasim Hadi, Romulus Costache, Quoc Bao Pham, Nguyễn Thị Thùy Linh, Rabiu Aliyu Abdulkadir, Duong Tran Anh and Shaban Ismael Albrka Ali‬ and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Hydrology and IEEE Access.

In The Last Decade

Jazuli Abdullahi

22 papers receiving 596 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jazuli Abdullahi Cyprus 10 356 253 180 131 89 22 612
Gözen Elkiran Cyprus 13 369 1.0× 350 1.4× 181 1.0× 142 1.1× 90 1.0× 19 732
Ahmed H. Birima Malaysia 14 356 1.0× 297 1.2× 131 0.7× 78 0.6× 67 0.8× 21 580
Pavitra Kumar Malaysia 14 292 0.8× 203 0.8× 103 0.6× 118 0.9× 88 1.0× 36 615
Mohammad Zeynoddin Canada 11 313 0.9× 222 0.9× 175 1.0× 56 0.4× 75 0.8× 21 530
Marzieh Fadaee Iran 6 318 0.9× 276 1.1× 191 1.1× 84 0.6× 47 0.5× 9 540
Akram Seifi Iran 14 415 1.2× 325 1.3× 168 0.9× 103 0.8× 90 1.0× 28 720
A. A. Masrur Ahmed Australia 15 482 1.4× 334 1.3× 183 1.0× 116 0.9× 114 1.3× 36 863
Sinan Jasim Hadi Türkiye 12 407 1.1× 353 1.4× 259 1.4× 108 0.8× 101 1.1× 18 692
Roozbeh Moazenzadeh Iran 11 339 1.0× 248 1.0× 259 1.4× 138 1.1× 95 1.1× 15 707
Seyed Mostafa Biazar Iran 17 424 1.2× 232 0.9× 341 1.9× 143 1.1× 158 1.8× 22 784

Countries citing papers authored by Jazuli Abdullahi

Since Specialization
Citations

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

Fields of papers citing papers by Jazuli Abdullahi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jazuli Abdullahi

This figure shows the co-authorship network connecting the top 25 collaborators of Jazuli Abdullahi. A scholar is included among the top collaborators of Jazuli Abdullahi 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 Jazuli Abdullahi. Jazuli Abdullahi 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.
Shiru, Mohammed Sanusi, et al.. (2024). Application of modified drastic model for oil spills pollution affecting water quality system in part of Niger delta region of Nigeria. Journal of Hydrology. 637. 131446–131446. 4 indexed citations
2.
Abdullahi, Jazuli, et al.. (2024). Assessment of Climate Change Impact on Precipitation Using Machine Learning Based Statistical Downscaling Method. SHILAP Revista de lepidopterología. 489. 4004–4004. 1 indexed citations
3.
Abba, Sani I., Quoc Bao Pham, Anurag Malik, et al.. (2024). Optimization of Extreme Learning Machine with Metaheuristic Algorithms for Modelling Water Quality Parameters of Tamburawa Water Treatment Plant in Nigeria. Water Resources Management. 39(3). 1377–1401. 3 indexed citations
4.
Abdullahi, Jazuli, et al.. (2023). Linear and non-linear ensemble concepts for pan evaporation modeling. Desalination and Water Treatment. 293. 67–81. 1 indexed citations
5.
Tulay, Pınar, et al.. (2022). Multi-region machine learning-based novel ensemble approaches for predicting COVID-19 pandemic in Africa. Environmental Science and Pollution Research. 30(2). 3621–3643. 16 indexed citations
6.
Manzar, Mohammad Saood, Mohammed Benaafi, Romulus Costache, et al.. (2022). New generation neurocomputing learning coupled with a hybrid neuro-fuzzy model for quantifying water quality index variable: A case study from Saudi Arabia. Ecological Informatics. 70. 101696–101696. 46 indexed citations
7.
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Elkiran, Gözen, et al.. (2021). Impact of climate change on hydro-climatological parameters in North Cyprus: application of artificial intelligence-based statistical downscaling models. Journal of Hydroinformatics. 23(6). 1395–1415. 14 indexed citations
10.
Abdullahi, Jazuli, et al.. (2020). Reference Evapotranspiration Modeling Using Heuristic Computing Model in Distinct Climate Stations. SHILAP Revista de lepidopterología. 6(1). 2 indexed citations
11.
Abdullahi, Jazuli, et al.. (2020). Data-Driven Techniques for Monthly Pan Evaporation Modeling in Iraq. SHILAP Revista de lepidopterología. 6(1). 2 indexed citations
12.
Abdullahi, Jazuli, et al.. (2020). Application of artificial intelligence based and multiple regression techniques for monthly precipitation modeling in coastal and inland stations. Desalination and Water Treatment. 177. 338–349. 3 indexed citations
13.
Abba, Sani I., Nguyễn Thị Thùy Linh, Jazuli Abdullahi, et al.. (2020). Hybrid Machine Learning Ensemble Techniques for Modeling Dissolved Oxygen Concentration. IEEE Access. 8. 157218–157237. 73 indexed citations
14.
Abdullahi, Jazuli, et al.. (2020). Virtual water trade in the semi-arid regions of Nigeria. IOP Conference Series Earth and Environmental Science. 614(1). 12074–12074. 2 indexed citations
15.
Nourani, Vahid, Gözen Elkiran, & Jazuli Abdullahi. (2019). Multi-station artificial intelligence based ensemble modeling of reference evapotranspiration using pan evaporation measurements. Journal of Hydrology. 577. 123958–123958. 111 indexed citations
16.
Nourani, Vahid, Gözen Elkiran, & Jazuli Abdullahi. (2019). Multi-step ahead modeling of reference evapotranspiration using a multi-model approach. Journal of Hydrology. 581. 124434–124434. 76 indexed citations
17.
Nourani, Vahid, et al.. (2019). Multi-region Modeling of Daily Global Solar Radiation with Artificial Intelligence Ensemble. Natural Resources Research. 28(4). 1217–1238. 50 indexed citations
18.
Elkiran, Gözen, Vahid Nourani, Sani I. Abba, & Jazuli Abdullahi. (2018). Artificial intelligence-based approaches for multi-station modelling of dissolve oxygen in river. SHILAP Revista de lepidopterología. 4(4). 439–450. 57 indexed citations
19.
Abdullahi, Jazuli & Gözen Elkiran. (2017). Prediction of the future impact of climate change on reference evapotranspiration in Cyprus using artificial neural network. Procedia Computer Science. 120. 276–283. 28 indexed citations
20.
Abba, Sani I., Sinan Jasim Hadi, & Jazuli Abdullahi. (2017). River water modelling prediction using multi-linear regression, artificial neural network, and adaptive neuro-fuzzy inference system techniques. Procedia Computer Science. 120. 75–82. 107 indexed citations

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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