Muhammad Sibtain

434 total citations
21 papers, 323 citations indexed

About

Muhammad Sibtain is a scholar working on Electrical and Electronic Engineering, Environmental Engineering and Water Science and Technology. According to data from OpenAlex, Muhammad Sibtain has authored 21 papers receiving a total of 323 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Electrical and Electronic Engineering, 9 papers in Environmental Engineering and 8 papers in Water Science and Technology. Recurrent topics in Muhammad Sibtain's work include Energy Load and Power Forecasting (10 papers), Hydrological Forecasting Using AI (8 papers) and Hydrology and Watershed Management Studies (8 papers). Muhammad Sibtain is often cited by papers focused on Energy Load and Power Forecasting (10 papers), Hydrological Forecasting Using AI (8 papers) and Hydrology and Watershed Management Studies (8 papers). Muhammad Sibtain collaborates with scholars based in China, Pakistan and Türkiye. Muhammad Sibtain's co-authors include Xianshan Li, Muhammad Imran Azam, Hassan Bashir, Halit Apaydın, Wenwu Li, Mohsin Nawaz, Tanveer Abbas, Ghulam Nabi, Qurat‐ul‐Ain and Hajar Feizi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Hydrology and Energy Conversion and Management.

In The Last Decade

Muhammad Sibtain

20 papers receiving 312 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Muhammad Sibtain China 11 171 129 97 77 66 21 323
Ergun Uzlu Türkiye 10 176 1.0× 97 0.8× 81 0.8× 99 1.3× 38 0.6× 21 474
Benjun Jia China 14 251 1.5× 99 0.8× 142 1.5× 68 0.9× 106 1.6× 41 513
Guangwen Ma China 12 237 1.4× 89 0.7× 140 1.4× 33 0.4× 77 1.2× 52 468
Annalisa Di Piazza Italy 8 230 1.3× 90 0.7× 69 0.7× 88 1.1× 131 2.0× 14 482
Lijian Sun China 11 96 0.6× 52 0.4× 34 0.4× 99 1.3× 34 0.5× 17 350
Yao Yu United States 10 109 0.6× 102 0.8× 40 0.4× 22 0.3× 45 0.7× 24 417
Weifeng Xu China 8 233 1.4× 42 0.3× 86 0.9× 45 0.6× 43 0.7× 15 345
Yusuf Essam Malaysia 7 72 0.4× 184 1.4× 147 1.5× 94 1.2× 76 1.2× 10 382
Luana Medeiros Marangon Lima Brazil 9 138 0.8× 40 0.3× 112 1.2× 24 0.3× 37 0.6× 20 282
Namal Rathnayake Japan 12 38 0.2× 171 1.3× 105 1.1× 68 0.9× 88 1.3× 41 411

Countries citing papers authored by Muhammad Sibtain

Since Specialization
Citations

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

Fields of papers citing papers by Muhammad Sibtain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Muhammad Sibtain

This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Sibtain. A scholar is included among the top collaborators of Muhammad Sibtain 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 Muhammad Sibtain. Muhammad Sibtain 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.
Sibtain, Muhammad, Xianshan Li, Fei Li, et al.. (2024). Improving Multivariate Runoff Prediction Through Multistage Novel Hybrid Models. Water Resources Management. 38(7). 2545–2564. 2 indexed citations
2.
Sibtain, Muhammad, et al.. (2024). Screening Disinfection Byproducts in Arid-Coastal Wastewater: A Workflow Using GC×GC-TOFMS, Passive Sampling, and NMF Deconvolution Algorithm. SHILAP Revista de lepidopterología. 14(2). 554–574. 2 indexed citations
3.
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Sibtain, Muhammad, et al.. (2024). A nature-inspired and noise-assisted feature extraction integrating spatiotemporal attention-based sequence2sequence for multivariate wind speed prediction. Stochastic Environmental Research and Risk Assessment. 39(1). 343–359. 2 indexed citations
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6.
Feizi, Hajar, et al.. (2022). Improving reservoir inflow prediction via rolling window and deep learning-based multi-model approach: case study from Ermenek Dam, Turkey. Stochastic Environmental Research and Risk Assessment. 36(10). 3149–3169. 15 indexed citations
7.
Tayyab, Muhammad, et al.. (2022). Monthly Streamflow Forecasting Using Decomposition-Based Hybridization with Two-step Verification Method Over the Mangla Watershed, Pakistan. Iranian Journal of Science and Technology Transactions of Civil Engineering. 47(1). 565–584. 5 indexed citations
8.
Sibtain, Muhammad, et al.. (2022). Multifaceted irradiance prediction by exploiting hybrid decomposition-entropy-Spatiotemporal attention based Sequence2Sequence models. Renewable Energy. 196. 648–682. 5 indexed citations
9.
Sibtain, Muhammad, et al.. (2021). A Multistage Hybrid Model ICEEMDAN-SE-VMD-RDPG for a Multivariate Solar Irradiance Forecasting. IEEE Access. 9. 37334–37363. 26 indexed citations
10.
Sibtain, Muhammad, et al.. (2021). Analytical modeling‐based optimal design of multilayered and multisegmented D‐type interior permanent magnet synchronous motor. International Transactions on Electrical Energy Systems. 31(5). 2 indexed citations
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Sibtain, Muhammad, Xianshan Li, Hassan Bashir, & Muhammad Imran Azam. (2021). A Hybrid Model for Runoff Prediction Using Variational Mode Decomposition and Artificial Neural Network. Water Resources. 48(5). 701–712. 12 indexed citations
13.
Sibtain, Muhammad, Xianshan Li, Hassan Bashir, & Muhammad Imran Azam. (2021). Hydropower exploitation for Pakistan's sustainable development: A SWOT analysis considering current situation, challenges, and prospects. Energy Strategy Reviews. 38. 100728–100728. 41 indexed citations
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Sibtain, Muhammad, Xianshan Li, Ghulam Nabi, Muhammad Imran Azam, & Hassan Bashir. (2020). Development of a Three-Stage Hybrid Model by Utilizing a Two-Stage Signal Decomposition Methodology and Machine Learning Approach to Predict Monthly Runoff at Swat River Basin, Pakistan. Discrete Dynamics in Nature and Society. 2020. 1–19. 24 indexed citations
16.
Sibtain, Muhammad, Xianshan Li, Muhammad Imran Azam, & Hassan Bashir. (2020). Applicability of a Three-Stage Hybrid Model byEmploying a Two-Stage Signal DecompositionApproach and a Deep Learning Methodologyfor Runoff Forecasting at Swat River Catchment,Pakistan. Polish Journal of Environmental Studies. 30(1). 369–384. 20 indexed citations
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Sibtain, Muhammad, et al.. (2018). Single and Three Phase Switch Ladder Multilevel Inverter. 1–6. 2 indexed citations
19.
Sibtain, Muhammad, et al.. (2018). Virtual Power Quality Analyzer Emphasizing the Distortion Factor in Power Factor Calculation. 13. 51–55. 1 indexed citations
20.
Yasin, Ghulam, Tariq Mahmood Ansari, Muhammad Sibtain, & Farah Naz Talpur. (2008). Analytical Studies on the Quality and Environmental Impact of Commercial Motor Gasoline Available in Multan Region of Pakistan. SHILAP Revista de lepidopterología. 5 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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