Azme Khamis
- Computational Mechanics top 5%
- Fluid Dynamics and Turbulent Flows 8
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- Nanofluid Flow and Heat Transfer 11
- Mechanical Engineering top 10%
- Heat Transfer Mechanisms 6
- Heat Transfer and Optimization 4
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- Stock Market Forecasting Methods 6
- Fuzzy and Soft Set Theory 6
- Forecasting Techniques and Applications 5
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- Energy Load and Power Forecasting 5
- Co-authors
- R. KandasamyI. MuhaiminZuhaimy IsmailRozaini RoslanKavikumar JacobIshak HashimMohd Saifullah RusimanMuhammad Akram
- Journals
- Mathematika (2 papers)Journal of Applied Sciences (2 papers)Applied Mathematics and Mechanics (2 papers)
- Partner nations
- MalaysiaUnited Arab EmiratesIndia
In The Last Decade
Azme Khamis
49 papers receiving 403 citations
Peers
Comparison fields: 5 of 108
- Computational Mechanics 169
- Biomedical Engineering 238
- Mechanical Engineering 185
- Management Science and Operations Research 55
- Modeling and Simulation 11
Countries citing papers authored by Azme Khamis
This map shows the geographic impact of Azme Khamis'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 Azme Khamis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Azme Khamis more than expected).
Fields of papers citing papers by Azme Khamis
This network shows the impact of papers produced by Azme Khamis. 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 Azme Khamis. The network helps show where Azme Khamis may publish in the future.
Co-authorship network
The 20 scholars most cited alongside Azme Khamis, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 2 | |
| 2 | 2019 | 6 | |
| 3 | INTEGER LINEAR PROGRAMMING ON PREFERENCE MAXIMIZED OF WORKFORCE SCHEDULING | 2018 | 1 |
| 4 | 2018 | 4 | |
| 5 | Comparative Study On Estimate House Price Using Statistical And Neural Network Model | 2014 | 10 |
| 6 | 2010 | 3 | |
| 7 | 2010 | 1 | |
| 8 | Fuzzy Bi-ideals in Ternary Semirings | 2009 | 5 |
| 9 | THE RIESZ THEOREM IN FUZZY n-NORMED LINEAR SPACES | 2009 | 0 |
| 10 | 2009 | 16 | |
| 11 | 2007 | 3 | |
| 12 | 2007 | 0 | |
| 13 | 2006 | 10 | |
| 14 | 2006 | 31 | |
| 15 | 2005 | 54 | |
| 16 | 2004 | 7 | |
| 17 | On Robust Environmental Quality Indices | 2004 | 2 |
| 18 | 2003 | 5 | |
| 19 | 2003 | 15 | |
| 20 | 2000 | 1 |
About Azme Khamis
Azme Khamis is a scholar working on Management Science and Operations Research, Statistics and Probability and Human Factors and Ergonomics, having authored 52 papers that have together received 456 indexed citations. Recurring topics across this work include Nanofluid Flow and Heat Transfer (11 papers), Fluid Dynamics and Turbulent Flows (8 papers), Heat Transfer Mechanisms (6 papers), Stock Market Forecasting Methods (6 papers), Fuzzy and Soft Set Theory (6 papers), Energy Load and Power Forecasting (5 papers), Forecasting Techniques and Applications (5 papers) and Heat Transfer and Optimization (4 papers). The work is most often cited by research in Computational Mechanics (169 citations), Biomedical Engineering (238 citations) and Mechanical Engineering (185 citations). Azme Khamis has collaborated with scholars based in Malaysia, United Arab Emirates and India. Frequent co-authors include R. Kandasamy, I. Muhaimin, Zuhaimy Ismail, Rozaini Roslan, Kavikumar Jacob, Ishak Hashim, Mohd Saifullah Rusiman, Muhammad Akram, Ani Shabri and Young Bae Jun. Their work appears in journals such as Mathematika, Journal of Applied Sciences, Applied Mathematics and Mechanics, Journal of Porous Media and International Journal of Thermal Sciences.
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.