J. J. Cárdenas
- Control and Systems Engineering top 10%
- Machine Fault Diagnosis Techniques 5
- Fault Detection and Control Systems 4
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- Energy Load and Power Forecasting 6
- Smart Grid Energy Management 4
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- Neural Networks and Applications 3
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- Building Energy and Comfort Optimization 2
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- Advanced Manufacturing and Logistics Optimization 2
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- Non-Destructive Testing Techniques 2
- Co-authors
- J. CusidóA. GarcíaFabio AndradeL. RomeralJordi Solé‐CasalsPere Martí-PuigKonstantinos KampouropoulosJ. A. Ortega
- Cited by
- Control and Systems EngineeringEnergy Engineering and Power TechnologySafety, Risk, Reliability and Quality
In The Last Decade
J. J. Cárdenas
20 papers receiving 277 citations
Peers
Comparison fields: 5 of 59
- Control and Systems Engineering 148
- Energy Engineering and Power Technology 11
- Safety, Risk, Reliability and Quality 27
- Electrical and Electronic Engineering 142
- Medical Laboratory Technology 3
Countries citing papers authored by J. J. Cárdenas
This map shows the geographic impact of J. J. Cárdenas'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 J. J. Cárdenas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. J. Cárdenas more than expected).
Fields of papers citing papers by J. J. Cárdenas
This network shows the impact of papers produced by J. J. Cárdenas. 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 J. J. Cárdenas. The network helps show where J. J. Cárdenas may publish in the future.
Co-authorship network
The 25 scholars most cited alongside J. J. Cárdenas, 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 | 2020 | 13 | |
| 2 | 2020 | 18 | |
| 3 | 2019 | 41 | |
| 4 | 2018 | 34 | |
| 5 | 2017 | 12 | |
| 6 | 2016 | 12 | |
| 7 | 2016 | 9 | |
| 8 | 2015 | 1 | |
| 9 | 2014 | 24 | |
| 10 | 2013 | 10 | |
| 11 | 2012 | 7 | |
| 12 | 2012 | 7 | |
| 13 | 2012 | 10 | |
| 14 | 2011 | 10 | |
| 15 | 2011 | 32 | |
| 16 | 2011 | 19 | |
| 17 | A multi-objective GA to demand-side management in an automated warehouse | 2009 | 4 |
| 18 | Stator short circuits detection in PMSM by means of Zhao-Atlas-Marks distribution and energy calculation | 2009 | 2 |
| 19 | 2009 | 17 | |
| 20 | 2009 | 7 |
About J. J. Cárdenas
J. J. Cárdenas is a scholar working on Control and Systems Engineering, Energy Engineering and Power Technology and Industrial and Manufacturing Engineering, having authored 20 papers that have together received 289 indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (6 papers), Machine Fault Diagnosis Techniques (5 papers), Smart Grid Energy Management (4 papers), Fault Detection and Control Systems (4 papers), Neural Networks and Applications (3 papers), Building Energy and Comfort Optimization (2 papers), Advanced Manufacturing and Logistics Optimization (2 papers) and Non-Destructive Testing Techniques (2 papers). The work is most often cited by research in Control and Systems Engineering (148 citations), Energy Engineering and Power Technology (11 citations) and Safety, Risk, Reliability and Quality (27 citations). J. J. Cárdenas has collaborated with scholars based in Spain, Colombia and Venezuela. Frequent co-authors include J. Cusidó, A. García, Fabio Andrade, L. Romeral, Jordi Solé‐Casals, Pere Martí-Puig, Konstantinos Kampouropoulos, J. A. Ortega, Luis Romeral and Cosmin Koch‐Ciobotaru. Their work appears in journals such as PLoS ONE, Expert Systems with Applications and IEEE Transactions on Energy Conversion.
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.