Ibrahim Elbatal

2.3k total citations
145 papers, 1.6k citations indexed

About

Ibrahim Elbatal is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Global and Planetary Change. According to data from OpenAlex, Ibrahim Elbatal has authored 145 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 125 papers in Statistics and Probability, 74 papers in Statistics, Probability and Uncertainty and 30 papers in Global and Planetary Change. Recurrent topics in Ibrahim Elbatal's work include Statistical Distribution Estimation and Applications (123 papers), Probabilistic and Robust Engineering Design (71 papers) and Statistical Methods and Bayesian Inference (36 papers). Ibrahim Elbatal is often cited by papers focused on Statistical Distribution Estimation and Applications (123 papers), Probabilistic and Robust Engineering Design (71 papers) and Statistical Methods and Bayesian Inference (36 papers). Ibrahim Elbatal collaborates with scholars based in Saudi Arabia, Egypt and Pakistan. Ibrahim Elbatal's co-authors include Mohammed Elgarhy, Faton Merovcı, Christophe Chesneau, Abdulhakim A. Al-Babtain, Ehab M. Almetwally, Gokarna Aryal, Naif Alotaibi, Salem A. Alyami, Farrukh Jamal and Mansour Shrahili and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Ibrahim Elbatal

125 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ibrahim Elbatal Saudi Arabia 22 1.5k 881 390 230 215 145 1.6k
Amal S. Hassan Egypt 23 1.9k 1.3× 1.3k 1.4× 419 1.1× 195 0.8× 187 0.9× 190 2.1k
Artur J. Lemonte Brazil 27 2.0k 1.3× 1.0k 1.2× 346 0.9× 182 0.8× 220 1.0× 114 2.2k
Hassan S. Bakouch Egypt 19 1.4k 0.9× 700 0.8× 270 0.7× 223 1.0× 468 2.2× 154 1.7k
Marcelo Bourguignon Brazil 20 1.3k 0.8× 649 0.7× 310 0.8× 156 0.7× 304 1.4× 109 1.5k
Mustafa Ç. Korkmaz Türkiye 22 1.1k 0.7× 572 0.6× 220 0.6× 167 0.7× 192 0.9× 65 1.2k
Emrah Altun Türkiye 22 1.3k 0.9× 629 0.7× 248 0.6× 220 1.0× 264 1.2× 93 1.4k
Sanku Dey India 28 2.1k 1.4× 1.5k 1.7× 360 0.9× 313 1.4× 151 0.7× 130 2.4k
Ehab M. Almetwally Egypt 26 2.2k 1.4× 1.2k 1.3× 448 1.1× 329 1.4× 291 1.4× 222 2.4k
Erhard Cramer Germany 25 2.5k 1.6× 1.7k 2.0× 483 1.2× 394 1.7× 227 1.1× 116 2.6k
Ahmed M. Gemeay Egypt 20 1.0k 0.7× 494 0.6× 184 0.5× 173 0.8× 145 0.7× 123 1.1k

Countries citing papers authored by Ibrahim Elbatal

Since Specialization
Citations

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

Fields of papers citing papers by Ibrahim Elbatal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ibrahim Elbatal

This figure shows the co-authorship network connecting the top 25 collaborators of Ibrahim Elbatal. A scholar is included among the top collaborators of Ibrahim Elbatal 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 Ibrahim Elbatal. Ibrahim Elbatal 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.
Elbatal, Ibrahim, et al.. (2025). Modelling on gross domestic product annual growth rate data by using time series, machine learning, and probability models. Journal of Radiation Research and Applied Sciences. 18(2). 101481–101481.
2.
Eid, Marwa M., et al.. (2024). Urban Noise Pollution: A Dataset for Spatiotemporal and Environmental Analysis. 1(2). 72–81. 1 indexed citations
3.
Elbatal, Ibrahim, et al.. (2024). Bayesian and E-Bayesian Reliability Analysis of Improved Adaptive Type-II Progressive Censored Inverted Lindley Data. IEEE Access. 12. 101829–101841. 2 indexed citations
4.
Elbatal, Ibrahim, et al.. (2023). Truncated Cauchy Power Kumaraswamy Generalized family of distributions: Theory and Applications. Statistics Optimization & Information Computing. 12(2). 364–380.
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Elbatal, Ibrahim, et al.. (2023). Stress–Strength Reliability Analysis for Different Distributions Using Progressive Type-II Censoring with Binomial Removal. Axioms. 12(11). 1054–1054. 7 indexed citations
8.
Elbatal, Ibrahim, et al.. (2023). Reliability Analysis and Its Applications for a Newly Improved Type-II Adaptive Progressive Alpha Power Exponential Censored Sample. Symmetry. 15(12). 2137–2137. 10 indexed citations
9.
Alotaibi, Naif, A. S. Al-Moisheer, Ibrahim Elbatal, et al.. (2023). Half Logistic Inverted Nadarajah–Haghighi Distribution under Ranked Set Sampling with Applications. Mathematics. 11(7). 1693–1693. 6 indexed citations
10.
Alotaibi, Naif, Ibrahim Elbatal, Mansour Shrahili, et al.. (2023). Statistical Inference for the Kavya–Manoharan Kumaraswamy Model under Ranked Set Sampling with Applications. Symmetry. 15(3). 587–587. 18 indexed citations
11.
Alotaibi, Naif, A. S. Al-Moisheer, Ibrahim Elbatal, et al.. (2023). Bayesian and Non-Bayesian Estimation for a New Extension of Power Topp–Leone Distribution under Ranked Set Sampling with Applications. Axioms. 12(8). 722–722. 7 indexed citations
12.
Alotaibi, Naif, Ibrahim Elbatal, Ehab M. Almetwally, et al.. (2022). Truncated Cauchy Power Weibull-G Class of Distributions: Bayesian and Non-Bayesian Inference Modelling for COVID-19 and Carbon Fiber Data. Mathematics. 10(9). 1565–1565. 32 indexed citations
13.
Bantan, Rashad A. R., et al.. (2022). Improved EDF-Based Tests for Weibull Distribution Using Ranked Set Sampling. Mathematics. 10(24). 4700–4700. 7 indexed citations
14.
15.
Alotaibi, Naif, Ibrahim Elbatal, Ehab M. Almetwally, et al.. (2022). Bivariate Step-Stress Accelerated Life Tests for the Kavya–Manoharan Exponentiated Weibull Model under Progressive Censoring with Applications. Symmetry. 14(9). 1791–1791. 15 indexed citations
16.
Al-Moisheer, A. S., et al.. (2021). Odd Inverse Power Generalized Weibull Generated Family of Distributions: Properties and Applications. Mathematical Problems in Engineering. 2021. 1–17. 26 indexed citations
17.
Shrahili, Mansour, Ibrahim Elbatal, & Mustapha Muhammad. (2018). The type I half-logistic Burr X distribution: theory and practice. The Journal of Nonlinear Sciences and Applications. 12(5). 262–277. 12 indexed citations
18.
Elbatal, Ibrahim, et al.. (2013). Parameter Estimations Based On Kumaraswamy Progressive Type II Censored Data with Random Removals. Journal of Modern Applied Statistical Methods. 12(2). 314–335. 8 indexed citations
19.
Elbatal, Ibrahim & Mohammed Elgarhy. (2013). Transmuted Quasi Lindley Distribution: A Generalization of the Quasi Lindley Distribution. 18(2). 22 indexed citations
20.
Elbatal, Ibrahim. (2012). ON SOME RELIABILITY CHARACTERIZATIONS OF MEMBER OF THE PEARSON AND ORD FAMILIES OF DISTRIBUTIONS. 3(4).

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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