W. Charytoniuk

812 total citations
10 papers, 642 citations indexed

About

W. Charytoniuk is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Astronomy and Astrophysics. According to data from OpenAlex, W. Charytoniuk has authored 10 papers receiving a total of 642 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Electrical and Electronic Engineering, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Astronomy and Astrophysics. Recurrent topics in W. Charytoniuk's work include Energy Load and Power Forecasting (7 papers), Image and Signal Denoising Methods (4 papers) and Lightning and Electromagnetic Phenomena (2 papers). W. Charytoniuk is often cited by papers focused on Energy Load and Power Forecasting (7 papers), Image and Signal Denoising Methods (4 papers) and Lightning and Electromagnetic Phenomena (2 papers). W. Charytoniuk collaborates with scholars based in United States and Poland. W. Charytoniuk's co-authors include M.-S. Chen, P. Van Olinda, Mo-Shing Chen, Wei‐Jen Lee, Joanicjusz Nazarko and Robert Broadwater and has published in prestigious journals such as IEEE Transactions on Power Systems, IEEE Transactions on Industry Applications and Electric Power Systems Research.

In The Last Decade

W. Charytoniuk

10 papers receiving 589 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
W. Charytoniuk United States	8	584	196	144	90	90	10	642
S.J. Kiartzis Greece	10	487 0.8×	233 1.2×	188 1.3×	82 0.9×	69 0.8×	12	609
H. Takara Japan	5	431 0.7×	168 0.9×	153 1.1×	55 0.6×	75 0.8×	8	478
Che Guan United States	6	659 1.1×	229 1.2×	183 1.3×	77 0.9×	189 2.1×	8	714
I.S. Moghram United States	5	594 1.0×	238 1.2×	167 1.2×	52 0.6×	99 1.1×	7	652
P. Van Olinda United States	8	488 0.8×	120 0.6×	96 0.7×	104 1.2×	57 0.6×	11	530
Jingrui Xie United States	11	808 1.4×	270 1.4×	208 1.4×	62 0.7×	100 1.1×	14	877
Suzanne M. Behr United States	5	420 0.7×	182 0.9×	127 0.9×	28 0.3×	62 0.7×	8	569
H.M. Al-Hamadi Kuwait	7	432 0.7×	185 0.9×	114 0.8×	47 0.5×	74 0.8×	10	472
Y.T. Cha United States	3	464 0.8×	163 0.8×	177 1.2×	49 0.5×	97 1.1×	4	513
Stylianos Sp. Pappas Greece	8	438 0.8×	203 1.0×	116 0.8×	63 0.7×	67 0.7×	19	541

Countries citing papers authored by W. Charytoniuk

Since Specialization

Citations

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

Fields of papers citing papers by W. Charytoniuk

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of W. Charytoniuk

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

All Works

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10 of 10 papers shown

1.

Nazarko, Joanicjusz, et al.. (2005). The Effect Of Expert Evaluations On The Efficiency Of Decision Processes In Power Distribution Systems. Jagiellonian University Repository (Jagiellonian University). 2. 606–610. 1 indexed citations

2.

Charytoniuk, W., et al.. (2002). Neural network design for short-term load forecasting. 554–561. 35 indexed citations

3.

Charytoniuk, W., et al.. (2002). Arcing fault detection in underground distribution networks feasibility study. 15–20. 10 indexed citations

4.

Charytoniuk, W., et al.. (2000). Neural-network-based demand forecasting in a deregulated environment. IEEE Transactions on Industry Applications. 36(3). 893–898. 36 indexed citations

5.

Charytoniuk, W. & M.-S. Chen. (2000). Very short-term load forecasting using artificial neural networks. IEEE Transactions on Power Systems. 15(1). 263–268. 208 indexed citations

6.

Chen, Mo-Shing, et al.. (2000). Arcing fault detection in underground distribution networks-feasibility study. IEEE Transactions on Industry Applications. 36(6). 1756–1761. 43 indexed citations

7.

Charytoniuk, W., et al.. (1999). Demand forecasting in power distribution systems using nonparametric probability density estimation. IEEE Transactions on Power Systems. 14(4). 1200–1206. 60 indexed citations

8.

Charytoniuk, W., et al.. (1998). Confidence interval construction for load forecast. Electric Power Systems Research. 48(2). 97–103. 7 indexed citations

9.

Charytoniuk, W., et al.. (1998). Nonparametric regression based short-term load forecasting. IEEE Transactions on Power Systems. 13(3). 725–730. 241 indexed citations

10.

Charytoniuk, W. & Joanicjusz Nazarko. (1994). An application of compound probability distributions to electric load modeling. Stochastic Analysis and Applications. 12(1). 31–40. 1 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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