Sujan Ghimire

2.5k total citations
42 papers, 1.8k citations indexed

About

Sujan Ghimire is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Environmental Engineering. According to data from OpenAlex, Sujan Ghimire has authored 42 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Electrical and Electronic Engineering, 21 papers in Artificial Intelligence and 11 papers in Environmental Engineering. Recurrent topics in Sujan Ghimire's work include Energy Load and Power Forecasting (27 papers), Solar Radiation and Photovoltaics (19 papers) and Hydrological Forecasting Using AI (7 papers). Sujan Ghimire is often cited by papers focused on Energy Load and Power Forecasting (27 papers), Solar Radiation and Photovoltaics (19 papers) and Hydrological Forecasting Using AI (7 papers). Sujan Ghimire collaborates with scholars based in Australia, Spain and Iraq. Sujan Ghimire's co-authors include Ravinesh C. Deo, Nawin Raj, Sancho Salcedo‐Sanz, David Casillas-Pérez, Jianchun Mi, Nathan Downs, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Thong Nguyen‐Huy, Xiaohui Tao and Ji Zhang and has published in prestigious journals such as Renewable and Sustainable Energy Reviews, Remote Sensing of Environment and Journal of Cleaner Production.

In The Last Decade

Sujan Ghimire

42 papers receiving 1.7k citations

Peers

Sujan Ghimire
Mawloud Guermoui Algeria
Nawin Raj Australia
Sudheer Ch India
Matteo De Felice Italy
C. Casanova‐Mateo Spain
Ramendra Prasad Fiji
Nadjem Bailek Algeria
Athanasios Sfetsos Greece
Georges Kariniotakis France
Rubén Urraca Spain
Mawloud Guermoui Algeria
Sujan Ghimire
Citations per year, relative to Sujan Ghimire Sujan Ghimire (= 1×) peers Mawloud Guermoui

Countries citing papers authored by Sujan Ghimire

Since Specialization
Citations

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

Fields of papers citing papers by Sujan Ghimire

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sujan Ghimire

This figure shows the co-authorship network connecting the top 25 collaborators of Sujan Ghimire. A scholar is included among the top collaborators of Sujan Ghimire 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 Sujan Ghimire. Sujan Ghimire 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.
Ghimire, Sujan, Ravinesh C. Deo, Ningxin Jiang, et al.. (2025). Explainable deep learning hybrid modeling framework for total suspended particles concentrations prediction. Atmospheric Environment. 347. 121079–121079. 2 indexed citations
2.
Casillas-Pérez, David, L. Cornejo-Bueno, Jorge Pérez‐Aracil, et al.. (2025). A comparative study of different kinematic wake models within metaheuristics for efficient wind farm layout optimization. Results in Engineering. 26. 105112–105112. 2 indexed citations
3.
Ghimire, Sujan, Ravinesh C. Deo, Konstantin Hopf, et al.. (2025). Half-hourly electricity price prediction model with explainable-decomposition hybrid deep learning approach. Energy and AI. 20. 100492–100492. 4 indexed citations
4.
Deo, Ravinesh C., et al.. (2025). Hybrid CNN–GRU model for hourly flood forecasting index: case studies from the Fiji islands. Stochastic Environmental Research and Risk Assessment. 39(5). 2203–2229. 1 indexed citations
5.
Joseph, Lionel, Sujan Ghimire, Ravinesh C. Deo, et al.. (2024). Explainable hybrid deep learning framework for enhancing multi-step solar ultraviolet-B radiation predictions. Atmospheric Environment. 343. 120951–120951. 2 indexed citations
6.
Ghimire, Sujan, Ravinesh C. Deo, David Casillas-Pérez, & Sancho Salcedo‐Sanz. (2024). Electricity demand error corrections with attention bi-directional neural networks. Energy. 291. 129938–129938. 15 indexed citations
7.
Ghimire, Sujan, Shahab Abdulla, Lionel Joseph, et al.. (2024). Explainable artificial intelligence-machine learning models to estimate overall scores in tertiary preparatory general science course. Computers and Education Artificial Intelligence. 7. 100331–100331. 5 indexed citations
8.
9.
Ghimire, Sujan, Ravinesh C. Deo, David Casillas-Pérez, et al.. (2024). Half-hourly electricity price prediction with a hybrid convolution neural network-random vector functional link deep learning approach. Applied Energy. 374. 123920–123920. 16 indexed citations
10.
Ghimire, Sujan, Mohanad S. AL‐Musaylh, Thong Nguyen‐Huy, et al.. (2024). Explainable deeply-fused nets electricity demand prediction model: Factoring climate predictors for accuracy and deeper insights with probabilistic confidence interval and point-based forecasts. Applied Energy. 378. 124763–124763. 8 indexed citations
11.
Ghimire, Sujan, Ravinesh C. Deo, S. Ali Pourmousavi, David Casillas-Pérez, & Sancho Salcedo‐Sanz. (2024). Point-based and probabilistic electricity demand prediction with a Neural Facebook Prophet and Kernel Density Estimation model. Engineering Applications of Artificial Intelligence. 135. 108702–108702. 8 indexed citations
12.
Ghimire, Sujan, Ravinesh C. Deo, David Casillas-Pérez, et al.. (2024). Electricity demand uncertainty modeling with Temporal Convolution Neural Network models. Renewable and Sustainable Energy Reviews. 209. 115097–115097. 1 indexed citations
13.
Ghimire, Sujan, Ravinesh C. Deo, David Casillas-Pérez, et al.. (2024). Probabilistic-based electricity demand forecasting with hybrid convolutional neural network-extreme learning machine model. Engineering Applications of Artificial Intelligence. 132. 107918–107918. 22 indexed citations
14.
Nguyen‐Huy, Thong, et al.. (2024). Copula-Probabilistic Flood Risk Analysis with an Hourly Flood Monitoring Index. Water. 16(11). 1560–1560. 2 indexed citations
15.
Ghimire, Sujan, Ravinesh C. Deo, David Casillas-Pérez, & Sancho Salcedo‐Sanz. (2023). Efficient daily electricity demand prediction with hybrid deep-learning multi-algorithm approach. Energy Conversion and Management. 297. 117707–117707. 25 indexed citations
16.
Ghimire, Sujan, Ravinesh C. Deo, David Casillas-Pérez, et al.. (2022). Deep learning CNN-LSTM-MLP hybrid fusion model for feature optimizations and daily solar radiation prediction. Measurement. 202. 111759–111759. 76 indexed citations
17.
18.
Ghimire, Sujan, Ravinesh C. Deo, David Casillas-Pérez, & Sancho Salcedo‐Sanz. (2022). Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise Deep Residual model for short-term multi-step solar radiation prediction. Renewable Energy. 190. 408–424. 46 indexed citations
19.
Ghimire, Sujan, Ravinesh C. Deo, David Casillas-Pérez, & Sancho Salcedo‐Sanz. (2022). Boosting solar radiation predictions with global climate models, observational predictors and hybrid deep-machine learning algorithms. Applied Energy. 316. 119063–119063. 61 indexed citations
20.
Ghimire, Sujan, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Aitazaz A. Farooque, et al.. (2021). Streamflow prediction using an integrated methodology based on convolutional neural network and long short-term memory networks. Scientific Reports. 11(1). 17497–17497. 184 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Mawloud Guermoui Breakdown of academic impact, for papers by Nawin Raj Breakdown of academic impact, for papers by Sudheer Ch Breakdown of academic impact, for papers by Matteo De Felice Breakdown of academic impact, for papers by C. Casanova‐Mateo Breakdown of academic impact, for papers by Ramendra Prasad Breakdown of academic impact, for papers by Nadjem Bailek Breakdown of academic impact, for papers by Athanasios Sfetsos Breakdown of academic impact, for papers by Georges Kariniotakis Breakdown of academic impact, for papers by Rubén Urraca
Rankless by CCL
2026