Seçkin Karasu
- Electrical and Electronic Engineering top 5%
- Artificial Intelligence top 2%
- Management Science and Operations Research top 1%
- Economics and Econometrics top 5%
- Control and Systems Engineering top 5%
- Topics
- Energy Load and Power Forecasting (9 papers)Power Quality and Harmonics (8 papers)Stock Market Forecasting Methods (7 papers)
In The Last Decade
Seçkin Karasu
21 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 139
- Electrical and Electronic Engineering 747
- Artificial Intelligence 561
- Management Science and Operations Research 483
- Economics and Econometrics 327
- Control and Systems Engineering 248
Countries citing papers authored by Seçkin Karasu
This map shows the geographic impact of Seçkin Karasu'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 Seçkin Karasu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seçkin Karasu more than expected).
Fields of papers citing papers by Seçkin Karasu
This network shows the impact of papers produced by Seçkin Karasu. 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 Seçkin Karasu. The network helps show where Seçkin Karasu may publish in the future.
Co-authorship network of co-authors of Seçkin Karasu
This figure shows the co-authorship network connecting the top 25 collaborators of Seçkin Karasu. A scholar is included among the top collaborators of Seçkin Karasu 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 Seçkin Karasu. Seçkin Karasu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 28 | |
| 3 | 13 | |
| 4 | A new forecasting model with wrapper-based feature selection approach using multi-objective optimization technique for chaotic crude oil time seriesbreakdown → | 425 |
| 5 | Recognition of COVID-19 disease from X-ray images by hybrid model consisting of 2D curvelet transform, chaotic salp swarm algorithm and deep learning techniquebreakdown → | 296 |
| 6 | A new hybrid model for wind speed forecasting combining long short-term memory neural network, decomposition methods and grey wolf optimizerbreakdown → | 505 |
| 7 | 43 | |
| 8 | 7 | |
| 9 | THE EFFECT OF KERNEL VALUES IN SUPPORT VECTOR MACHINE TO FORECASTING PERFORMANCE OF FINANCIAL TIME SERIES | 77 |
| 10 | 5 | |
| 11 | 110 | |
| 12 | Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniquesbreakdown → | 323 |
| 13 | 1 | |
| 14 | 79 | |
| 15 | 4 | |
| 16 | 35 | |
| 17 | ESTIMATION OF FAST VARIED WIND SPEED BASED ON NARX NEURAL NETWORK BY USING CURVE FITTING | 54 |
| 18 | 58 | |
| 19 | 7 | |
| 20 | 11 |
About Seçkin Karasu
Seçkin Karasu is a scholar working on Management Science and Operations Research, Electrical and Electronic Engineering and Civil and Structural Engineering, having authored 21 papers that have together received 2.3k indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (9 papers), Power Quality and Harmonics (8 papers) and Stock Market Forecasting Methods (7 papers). The work is most often cited by research in Management Science and Operations Research (483 citations), Artificial Intelligence (561 citations) and Health Informatics (23 citations). Seçkin Karasu has collaborated with scholars based in Türkiye, Italy and Canada. Frequent co-authors include Aytaç Altan, Stelios Bekiros, Enrico Zio, Wasim Ahmad, Zehra Saraç, Rıfat Hacıoğlu and Mehmet Pekkaya. Their work appears in journals such as Energy, Applied Soft Computing and Chaos Solitons & Fractals.
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.