Shahram Hanifi

694 total citations · 1 hit paper
6 papers, 445 citations indexed

About

Shahram Hanifi is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Shahram Hanifi has authored 6 papers receiving a total of 445 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Electrical and Electronic Engineering, 2 papers in Artificial Intelligence and 1 paper in Control and Systems Engineering. Recurrent topics in Shahram Hanifi's work include Energy Load and Power Forecasting (5 papers), Electric Power System Optimization (4 papers) and Solar Radiation and Photovoltaics (2 papers). Shahram Hanifi is often cited by papers focused on Energy Load and Power Forecasting (5 papers), Electric Power System Optimization (4 papers) and Solar Radiation and Photovoltaics (2 papers). Shahram Hanifi collaborates with scholars based in United Kingdom. Shahram Hanifi's co-authors include Saeid Lotfian, Xiaolei Liu, Zi Lin, Hossein Zare‐Behtash, Andrea Cammarano, Don McGlinchey, Babakalli Alkali and Gordon B. Lindsay and has published in prestigious journals such as Renewable Energy, Energies and Applied Sciences.

In The Last Decade

Shahram Hanifi

6 papers receiving 436 citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A Critical Review of Wind Power Forecasting Methods—Past, Present and Future

2020 266 citations Shahram Hanifi, Xiaolei Liu et al. Energies profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shahram Hanifi United Kingdom	4	343	177	90	49	45	6	445
Binhua Dai China	8	398 1.2×	185 1.0×	75 0.8×	44 0.9×	36 0.8×	10	468
Santhosh Madasthu India	10	418 1.2×	172 1.0×	142 1.6×	71 1.4×	72 1.6×	19	510
Jingyi Han China	5	282 0.8×	108 0.6×	85 0.9×	68 1.4×	48 1.1×	12	385
J.-C. Peng China	6	435 1.3×	151 0.9×	67 0.7×	46 0.9×	50 1.1×	8	561
K U Jaseena India	6	249 0.7×	132 0.7×	52 0.6×	61 1.2×	44 1.0×	12	367
Kiran Teeparthi India	14	435 1.3×	145 0.8×	66 0.7×	39 0.8×	116 2.6×	46	547
Xiangang Peng China	12	485 1.4×	176 1.0×	79 0.9×	59 1.2×	117 2.6×	33	585
Chintham Venkaiah India	9	453 1.3×	150 0.8×	112 1.2×	62 1.3×	121 2.7×	25	530
Ming Pei China	11	473 1.4×	215 1.2×	83 0.9×	49 1.0×	35 0.8×	20	558
Zexian Sun China	7	304 0.9×	123 0.7×	44 0.5×	30 0.6×	78 1.7×	8	374

Countries citing papers authored by Shahram Hanifi

Since Specialization

Citations

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

Fields of papers citing papers by Shahram Hanifi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shahram Hanifi

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

All Works

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6 of 6 papers shown

1.

Hanifi, Shahram, et al.. (2025). Optimizing Energy and Air Consumption in Smart Manufacturing: An Industrial Internet of Things-Based Monitoring and Efficiency Enhancement Solution. Applied Sciences. 15(6). 3222–3222. 1 indexed citations

2.

Hanifi, Shahram, et al.. (2024). Advancements in predictive maintenance modelling for industrial electrical motors: Integrating machine learning and sensor technologies. Measurement Sensors. 38. 101473–101473. 2 indexed citations

3.

Hanifi, Shahram, Hossein Zare‐Behtash, Andrea Cammarano, & Saeid Lotfian. (2023). Offshore wind power forecasting based on WPD and optimised deep learning methods. Renewable Energy. 218. 119241–119241. 43 indexed citations

4.

Hanifi, Shahram, et al.. (2023). Advanced hyperparameter optimization of deep learning models for wind power prediction. Renewable Energy. 221. 119700–119700. 99 indexed citations

5.

Hanifi, Shahram, Saeid Lotfian, Hossein Zare‐Behtash, & Andrea Cammarano. (2022). Offshore Wind Power Forecasting—A New Hyperparameter Optimisation Algorithm for Deep Learning Models. Energies. 15(19). 6919–6919. 34 indexed citations

6.

Hanifi, Shahram, Xiaolei Liu, Zi Lin, & Saeid Lotfian. (2020). A Critical Review of Wind Power Forecasting Methods—Past, Present and Future. Energies. 13(15). 3764–3764. 266 indexed citations breakdown →

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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