Imo Eyoh

22 papers receiving 327 citations

Peers

Imo Eyoh
Comparison fields: 5 of 68
  • Statistics and Probability 61
  • Ocean Engineering 101
  • Artificial Intelligence 153
  • Management Science and Operations Research 55
  • Software 12
Replace Wojciech Cholewa with:
Wojciech Cholewa Poland
E. McCormick United States
Derya B. Özyurt United States
Naresh Iyer United States
Christian Schmidt Germany
Guo Bo China
Liang-Sian Lin Taiwan
Durga Rao Karanki Switzerland
Binbin Xu China
Imo Eyoh relative to Wojciech Cholewa Poland Wojciech Cholewa's profile →
Citations per field
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Citations per year

Countries citing papers authored by Imo Eyoh

Since Specialization
Citations

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

Fields of papers citing papers by Imo Eyoh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside Imo Eyoh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Imo Eyoh Line = papers co-authored together Imo Eyoh links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201877
2 202172
3 202150
4 201739
5 201624
6 201719
7 20239
8 20198
9 20178
10 20207
11 20203
12 20213
13 20212
14 20202
15 20202
16 20202
17 20211
18
A Sliding Mode Control Learning of Interval Type-2 Intuitionistic Fuzzy Logic for Non-Linear System Prediction
20201
19
Time series forecasting with interval type-2 intuitionistic fuzzy logic systems
20171
20
Object Oriented Database Management System: A UML Design Approach.
20091

About Imo Eyoh

Imo Eyoh is a scholar working on Artificial Intelligence, Statistics and Probability, Information Systems, Management Science and Operations Research and Computer Networks and Communications, having authored 22 papers that have together received 333 indexed citations. Recurring topics across this work include Fuzzy Logic and Control Systems (14 papers), Neural Networks and Applications (12 papers), Fuzzy Systems and Optimization (10 papers), Stock Market Forecasting Methods (3 papers), Software Reliability and Analysis Research (2 papers), Drilling and Well Engineering (2 papers), Software Engineering Research (2 papers) and Hydraulic Fracturing and Reservoir Analysis (2 papers). The work is most often cited by research in Statistics and Probability (61 citations), Ocean Engineering (101 citations), Artificial Intelligence (153 citations), Management Science and Operations Research (55 citations) and Software (12 citations). Imo Eyoh has collaborated with scholars based in United Kingdom, Nigeria and China. Frequent co-authors include Robert John, Geert De Maere, Udoinyang G. Inyang, Erdal Kayacan, Moses E. Ekpenyong, Okorie Ekwe Agwu, Julius U. Akpabio, Jerry M. Mendel, Roy Kalawsky and Josef Ehling. Their work appears in journals such as IEEE Transactions on Fuzzy Systems, Journal of Natural Gas Science and Engineering, International Journal of Fuzzy Systems, Journal of Petroleum Science and Engineering and Solid State Technology.

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.

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