Henrique S. Hippert
- Electrical and Electronic Engineering top 2%
- Management Science and Operations Research top 0.5%
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 5%
- Environmental Engineering top 5%
- Topics
- Energy Load and Power Forecasting (8 papers)Hydrological Forecasting Using AI (4 papers)Neural Networks and Applications (3 papers)
- Cited by
- Management Science and Operations ResearchElectrical and Electronic EngineeringEnvironmental Engineering
- Partner nations
- BrazilUnited Kingdom
In The Last Decade
Henrique S. Hippert
9 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 86
- Electrical and Electronic Engineering 1.7k
- Management Science and Operations Research 746
- Artificial Intelligence 505
- Computer Vision and Pattern Recognition 284
- Environmental Engineering 268
Countries citing papers authored by Henrique S. Hippert
This map shows the geographic impact of Henrique S. Hippert'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 Henrique S. Hippert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Henrique S. Hippert more than expected).
Fields of papers citing papers by Henrique S. Hippert
This network shows the impact of papers produced by Henrique S. Hippert. 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 Henrique S. Hippert. The network helps show where Henrique S. Hippert may publish in the future.
Co-authorship network of co-authors of Henrique S. Hippert
This figure shows the co-authorship network connecting the top 25 collaborators of Henrique S. Hippert. A scholar is included among the top collaborators of Henrique S. Hippert 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 Henrique S. Hippert. Henrique S. Hippert is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 16 | |
| 2 | 22 | |
| 3 | Short-term load forecasting by artificial neural ne tworks specified by genetic algorithms - a simulation stud y over a Brazilian dataset. | 4 |
| 4 | Univariate versus Multivariate Models for Short-term Electricity Load Forecasting | 1 |
| 5 | 74 | |
| 6 | 85 | |
| 7 | 31 | |
| 8 | Neural networks for short-term load forecasting: a review and evaluationbreakdown → | 1659 |
| 9 | 45 |
About Henrique S. Hippert
Henrique S. Hippert is a scholar working on Management Science and Operations Research, Environmental Engineering and Computer Vision and Pattern Recognition, having authored 9 papers that have together received 1.9k indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (8 papers), Hydrological Forecasting Using AI (4 papers) and Neural Networks and Applications (3 papers). The work is most often cited by research in Management Science and Operations Research (746 citations), Electrical and Electronic Engineering (1.7k citations) and Environmental Engineering (268 citations). Henrique S. Hippert has collaborated with scholars based in Brazil and United Kingdom. Frequent co-authors include Reinaldo Castro Souza, Carlos E. Pedreira, James W. Taylor, Derek W. Bunn and Leonardo Goliatt. Their work appears in journals such as Scientific Reports, IEEE Transactions on Power Systems and Neural Networks.
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.