E. Chiodo

1.1k total citations
87 papers, 847 citations indexed

About

E. Chiodo is a scholar working on Safety, Risk, Reliability and Quality, Electrical and Electronic Engineering and Statistics, Probability and Uncertainty. According to data from OpenAlex, E. Chiodo has authored 87 papers receiving a total of 847 indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Safety, Risk, Reliability and Quality, 37 papers in Electrical and Electronic Engineering and 29 papers in Statistics, Probability and Uncertainty. Recurrent topics in E. Chiodo's work include Power System Reliability and Maintenance (34 papers), Probabilistic and Robust Engineering Design (26 papers) and Reliability and Maintenance Optimization (25 papers). E. Chiodo is often cited by papers focused on Power System Reliability and Maintenance (34 papers), Probabilistic and Robust Engineering Design (26 papers) and Reliability and Maintenance Optimization (25 papers). E. Chiodo collaborates with scholars based in Italy, Pakistan and United States. E. Chiodo's co-authors include D. Lauria, Giovanni Mazzanti, Fabio Mottola, Pasquale De Falco, Luigi Pio Di Noia, Cosimo Pisani, Mario Pagano, Natascia Andrenacci, Giorgio Maria Giannuzzi and Gabriele Malgaroli and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, Applied Energy and IEEE Access.

In The Last Decade

E. Chiodo

81 papers receiving 821 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
E. Chiodo Italy 16 488 291 196 189 150 87 847
Pasquale De Falco Italy 18 778 1.6× 80 0.3× 130 0.7× 41 0.2× 251 1.7× 62 945
F. Spinato United Kingdom 8 462 0.9× 413 1.4× 696 3.6× 108 0.6× 34 0.2× 9 1.2k
Omid Alavi Iran 12 541 1.1× 37 0.1× 56 0.3× 36 0.2× 49 0.3× 30 879
Wijarn Wangdee Canada 16 877 1.8× 787 2.7× 202 1.0× 129 0.7× 21 0.1× 51 1.0k
Andrija Volkanovski Slovenia 10 149 0.3× 263 0.9× 79 0.4× 246 1.3× 15 0.1× 26 553
Fabio Mottola Italy 21 1.2k 2.5× 34 0.1× 845 4.3× 21 0.1× 282 1.9× 105 1.4k
Shilie Weng China 17 281 0.6× 37 0.1× 166 0.8× 35 0.2× 32 0.2× 85 899
Robert John Millar Finland 19 734 1.5× 114 0.4× 351 1.8× 11 0.1× 49 0.3× 66 868
Hans Bludszuweit Spain 8 849 1.7× 135 0.5× 241 1.2× 22 0.1× 90 0.6× 22 926
J.A. Jardini Brazil 12 692 1.4× 81 0.3× 283 1.4× 9 0.0× 72 0.5× 60 834

Countries citing papers authored by E. Chiodo

Since Specialization
Citations

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

Fields of papers citing papers by E. Chiodo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of E. Chiodo

This figure shows the co-authorship network connecting the top 25 collaborators of E. Chiodo. A scholar is included among the top collaborators of E. Chiodo 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 E. Chiodo. E. Chiodo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Chiodo, E. & Luigi Pio Di Noia. (2024). Bayes Reliability Estimation of Motor Drives Redundant Configuration. 1. 455–459.
2.
Chiodo, E., et al.. (2024). Linear Quadratic Gaussian Integral Control for Secondary Voltage Regulation. Energies. 18(1). 4–4.
3.
Chiodo, E., et al.. (2023). A Review on Wind Speed Extreme Values Modeling and Bayes Estimation for Wind Power Plant Design and Construction. Energies. 16(14). 5456–5456. 7 indexed citations
4.
Chiodo, E., Pasquale De Falco, & Luigi Pio Di Noia. (2022). Probabilistic Modeling of Li-Ion Battery Remaining Useful Life. IEEE Transactions on Industry Applications. 58(4). 5214–5226. 18 indexed citations
5.
Chiodo, E., Pasquale De Falco, & Luigi Pio Di Noia. (2020). Probabilistic Modeling of Li-Ion Battery Remaining Useful Life. CINECA IRIS Institutial research information system (Parthenope University of Naples). 1–6. 1 indexed citations
6.
Chiodo, E. & Luigi Pio Di Noia. (2020). Stochastic Extreme Wind Speed Modeling and Bayes Estimation under the Inverse Rayleigh Distribution. Applied Sciences. 10(16). 5643–5643. 6 indexed citations
7.
Chiodo, E., D. Lauria, Fabio Mottola, & Natascia Andrenacci. (2019). Battery Conditional Reliability Function Under an Inverse Gaussian model and its Bayes Estimation. 8. 550–555. 2 indexed citations
8.
Chiodo, E., Pasquale De Falco, Luigi Pio Di Noia, & Fabio Mottola. (2018). Inverse Log-logistic distribution for Extreme Wind Speed modeling: Genesis, identification and Bayes estimation. AIMS energy. 6(6). 926–948. 17 indexed citations
9.
Chiodo, E., Luigi Pio Di Noia, & Fabio Mottola. (2018). Electrical insulation components reliability assessment and practical Bayesian estimation under a Log-Logistic model. International Journal of Engineering & Technology. 7(3). 1072–1072. 3 indexed citations
10.
Chiodo, E. & Pasquale De Falco. (2016). Bayesian estimation of inverse burr stress-strength model for power system components reliability assessment. CINECA IRIS Institutial research information system (Parthenope University of Naples). 348–353. 5 indexed citations
11.
Chiodo, E., Giovanni Mazzanti, & Mohammad Karimian. (2015). Bayes estimation of Inverse Weibull distribution for extreme wind speed prediction. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 639–646. 10 indexed citations
12.
Chiodo, E., Luigi Pio Di Noia, & D. Lauria. (2014). Stochastic modelling of electrochemical batteries for smart grids applications. 8. 1071–1076. 6 indexed citations
13.
Chiodo, E., D. Lauria, Cosimo Pisani, & D. Villacci. (2013). Transient Stability Margins Evaluation Based Upon Probabilistic Approach. International Review of Electrical Engineering (IREE). 8(2). 752–761. 8 indexed citations
14.
Chiodo, E., et al.. (2013). Experimental performances and life cycle estimation of hybrid electric storage systems. ENEA Open Archive (National Agency for New Technologies, Energy and Sustainable Economic Development). 8. 614–619. 10 indexed citations
15.
Chiodo, E.. (2013). The Burr XII Model and its Bayes Estimation for Wind Power Production Assessment. 8(2). 737–751. 10 indexed citations
16.
17.
Chiodo, E. & D. Lauria. (2009). On-line estimation of wind farm transient stability. 1. 746–750. 6 indexed citations
18.
Pucci, Marcello, Maurizio Cirrincione, Vittorio Cecconi, Mario Pagano, & E. Chiodo. (2003). Definition and Bayes estimation of stochastic safety index: application to cable-way point. Dialnet (Universidad de la Rioja). 11(4). 217–226. 2 indexed citations
19.
Chiodo, E., et al.. (2002). Dynamic discriminant analysis for predictive maintenance of electrical components subjected to stochastic wear. COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering. 21(1). 98–115. 7 indexed citations
20.
Chiodo, E., Francesco Gagliardi, Massimo La Scala, & D. Lauria. (1999). Probabilistic on-line transient stability analysis. IEE Proceedings - Generation Transmission and Distribution. 146(2). 176–176. 9 indexed citations

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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