B. K. Raghavendra
About
In The Last Decade
B. K. Raghavendra
8 papers receiving 277 citations
Peers
Comparison fields: 5 of 48
- Plant Science 259
- Analytical Chemistry 98
- Ecology 32
- Artificial Intelligence 25
- Information Systems 15
Countries citing papers authored by B. K. Raghavendra
This map shows the geographic impact of B. K. Raghavendra'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 B. K. Raghavendra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites B. K. Raghavendra more than expected).
Fields of papers citing papers by B. K. Raghavendra
This network shows the impact of papers produced by B. K. Raghavendra. 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 B. K. Raghavendra. The network helps show where B. K. Raghavendra may publish in the future.
Co-authorship network of co-authors of B. K. Raghavendra
This figure shows the co-authorship network connecting the top 25 collaborators of B. K. Raghavendra. A scholar is included among the top collaborators of B. K. Raghavendra 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 B. K. Raghavendra. B. K. Raghavendra is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 3 | |
| 3 | 209 | |
| 4 | 1 | |
| 5 | 74 | |
| 6 | EVALUATING THE PERFORMANCE OF NEURAL NETWORK USING FEATURE SELECTION METHODS ON PIMA INDIAN DIABETES DATASET | 1 |
| 7 | 12 | |
| 8 | Evaluation of Feature Selection Methods for Predictive Modeling Using Neural Networks in Credits Scoring | 8 |
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.