Ho-Sung Park
- Artificial Intelligence top 5%
- Statistical and Nonlinear Physics top 10%
- Control and Systems Engineering
- Signal Processing top 10%
- Computer Vision and Pattern Recognition
- Co-authors
- Sung‐Kwun OhWitold PedryczSue MoonChanghyun LeeHaewoon KwakJi‐Hwan KimDaeseon ChoiJeong‐Sik Park
- Topics
- Neural Networks and Applications (15 papers)Fuzzy Logic and Control Systems (14 papers)Speech Recognition and Synthesis (8 papers)
- Partner nations
- South KoreaCanadaPoland
In The Last Decade
Ho-Sung Park
31 papers receiving 415 citations
Peers
Comparison fields: 5 of 71
- Artificial Intelligence 272
- Statistical and Nonlinear Physics 55
- Control and Systems Engineering 48
- Signal Processing 48
- Computer Vision and Pattern Recognition 45
Countries citing papers authored by Ho-Sung Park
This map shows the geographic impact of Ho-Sung Park'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 Ho-Sung Park with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ho-Sung Park more than expected).
Fields of papers citing papers by Ho-Sung Park
This network shows the impact of papers produced by Ho-Sung Park. 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 Ho-Sung Park. The network helps show where Ho-Sung Park may publish in the future.
Co-authorship network of co-authors of Ho-Sung Park
This figure shows the co-authorship network connecting the top 25 collaborators of Ho-Sung Park. A scholar is included among the top collaborators of Ho-Sung Park 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 Ho-Sung Park. Ho-Sung Park is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 0 | |
| 3 | 4 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 17 | |
| 8 | 5 | |
| 9 | 3 | |
| 10 | 1 | |
| 11 | 2 | |
| 12 | 33 | |
| 13 | 1 | |
| 14 | Self-Organizing Polynomial Neural Networks Based on Genetically Optimized Multi-Layer Perceptron Architecture | 18 |
| 15 | Fuzzy Relation-Based Fuzzy Neural-Networks Using a Hybrid Identification Algorithm | 9 |
| 16 | Rule-Based Fuzzy-Neural Networks Using the Identification Algorithm of the GA Hybrid Scheme | 1 |
| 17 | Multi-FNN Identification Based on HCM Clustering and Evolutionary Fuzzy Granulation | 16 |
| 18 | 20 | |
| 19 | 57 | |
| 20 | Design of Improved Multi-FNN for Nonlinear System Modeling | 3 |
About Ho-Sung Park
Ho-Sung Park is a scholar working on Artificial Intelligence, Signal Processing and Developmental Biology, having authored 38 papers that have together received 452 indexed citations. Recurring topics across this work include Neural Networks and Applications (15 papers), Fuzzy Logic and Control Systems (14 papers) and Speech Recognition and Synthesis (8 papers). The work is most often cited by research in Artificial Intelligence (272 citations), Signal Processing (48 citations) and Statistical and Nonlinear Physics (55 citations). Ho-Sung Park has collaborated with scholars based in South Korea, Canada and Poland. Frequent co-authors include Sung‐Kwun Oh, Witold Pedrycz, Sue Moon, Changhyun Lee, Haewoon Kwak, Ji‐Hwan Kim, Daeseon Choi, Jeong‐Sik Park, Gil‐Jin Jang and Dong-Hyun Lee. Their work appears in journals such as Expert Systems with Applications, Fuzzy Sets and Systems and Neurocomputing.
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.