K. Uezato

4.7k total citations
118 papers, 3.8k citations indexed

About

K. Uezato is a scholar working on Electrical and Electronic Engineering, Control and Systems Engineering and Mechanical Engineering. According to data from OpenAlex, K. Uezato has authored 118 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 98 papers in Electrical and Electronic Engineering, 52 papers in Control and Systems Engineering and 15 papers in Mechanical Engineering. Recurrent topics in K. Uezato's work include Sensorless Control of Electric Motors (45 papers), Electric Motor Design and Analysis (41 papers) and Multilevel Inverters and Converters (22 papers). K. Uezato is often cited by papers focused on Sensorless Control of Electric Motors (45 papers), Electric Motor Design and Analysis (41 papers) and Multilevel Inverters and Converters (22 papers). K. Uezato collaborates with scholars based in Japan, Singapore and India. K. Uezato's co-authors include Tomonobu Senjyu, Mummadi Veerachary, Toshihisa Funabashi, N. Urasaki, Toshihisa Funabashi, H. Takara, K. Shimabukuro, Paras Mandal, H. Miyazato and H. Fujita and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, IEEE Transactions on Power Electronics and IEEE Transactions on Power Systems.

In The Last Decade

K. Uezato

115 papers receiving 3.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
K. Uezato Japan 30 3.1k 1.3k 857 609 355 118 3.8k
Toshihisa Funabashi Japan 34 3.9k 1.2× 2.1k 1.6× 317 0.4× 511 0.8× 246 0.7× 215 4.5k
Sishaj P. Simon India 28 2.4k 0.8× 693 0.5× 930 1.1× 858 1.4× 158 0.4× 132 3.1k
A. Keyhani United States 38 4.3k 1.4× 3.0k 2.3× 642 0.7× 469 0.8× 358 1.0× 189 5.2k
Shanxu Duan China 33 4.8k 1.5× 2.3k 1.8× 1.1k 1.3× 810 1.3× 999 2.8× 132 5.3k
Liuchen Chang Canada 42 6.9k 2.2× 4.3k 3.3× 1.1k 1.2× 290 0.5× 676 1.9× 390 7.5k
Loredana Cristaldi Italy 25 1.4k 0.4× 593 0.5× 722 0.8× 553 0.9× 199 0.6× 174 2.3k
Kai Strunz Germany 40 5.5k 1.8× 4.1k 3.1× 604 0.7× 128 0.2× 1.0k 2.9× 185 6.6k
M. A. Mahmud Australia 37 4.6k 1.5× 3.9k 3.0× 635 0.7× 220 0.4× 466 1.3× 304 5.5k
Guoqing Li China 28 3.2k 1.0× 1.3k 1.0× 243 0.3× 140 0.2× 283 0.8× 149 3.8k
Ahmed A. Zaki Diab Egypt 29 2.0k 0.7× 1.2k 0.9× 844 1.0× 676 1.1× 291 0.8× 146 3.0k

Countries citing papers authored by K. Uezato

Since Specialization
Citations

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

Fields of papers citing papers by K. Uezato

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of K. Uezato

This figure shows the co-authorship network connecting the top 25 collaborators of K. Uezato. A scholar is included among the top collaborators of K. Uezato 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 K. Uezato. K. Uezato 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.
Mandal, Paras, Tomonobu Senjyu, K. Uezato, & Toshihisa Funabashi. (2005). Several-hours-ahead electricity price and load forecasting using neural networks. IEEE Power Engineering Society General Meeting, 2005. 2205–2212. 36 indexed citations
2.
Senjyu, Tomonobu, Paras Mandal, K. Uezato, & Toshihisa Funabashi. (2004). Next day load curve forecasting using recurrent neural network structure. IEE Proceedings - Generation Transmission and Distribution. 151(3). 388–388. 53 indexed citations
3.
Senjyu, Tomonobu, K. Shimabukuro, K. Uezato, & Toshihisa Funabashi. (2004). A fast technique for unit commitment problem by extended priority list. 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491). 1108–1108. 2 indexed citations
4.
Veerachary, Mummadi, Tomonobu Senjyu, & K. Uezato. (2003). Maximum power point tracking of coupled inductor interleaved boost converter supplied PV system. IEE Proceedings - Electric Power Applications. 150(1). 71–80. 77 indexed citations
5.
Senjyu, Tomonobu, et al.. (2003). Parameter measurement for synchronous reluctance motors considering stator and rotor iron loss. 126–128. 3 indexed citations
6.
Veerachary, Mummadi, Tomonobu Senjyu, & K. Uezato. (2003). Neural-network-based maximum-power-point tracking of coupled-inductor interleaved-boost-converter-supplied pv system using fuzzy controller. IEEE Transactions on Industrial Electronics. 50(4). 749–758. 393 indexed citations
7.
Senjyu, Tomonobu, H. Miyazato, & K. Uezato. (2002). Quick and precise position control of ultrasonic motors with two control inputs. 1. 415–420. 6 indexed citations
8.
Uezato, K., et al.. (2002). Unity power factor AC/DC converter using full-order state observer. 2. 761–766. 1 indexed citations
9.
Veerachary, Mummadi, Tomonobu Senjyu, & K. Uezato. (2002). Voltage-based maximum power point tracking control of PV system. IEEE Transactions on Aerospace and Electronic Systems. 38(1). 262–270. 171 indexed citations
10.
Urasaki, N., Tomonobu Senjyu, & K. Uezato. (2002). Relationship of parallel model and series model for PMSM including iron loss. 2. 788–793. 12 indexed citations
11.
Senjyu, Tomonobu, et al.. (2002). Adaptive control for multi-machine power systems using genetic algorithm and neural network. 2000 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.00CH37077). 2. 1342–1347. 1 indexed citations
12.
Uezato, K., et al.. (2002). Vector control of a synchronous reluctance motor including iron loss. 110 d. 377–382. 6 indexed citations
13.
Senjyu, Tomonobu, et al.. (2002). Vector control of permanent magnet synchronous motors including stator iron loss. 1–5. 5 indexed citations
14.
15.
Veerachary, Mummadi, Tomonobu Senjyu, & K. Uezato. (2001). Maximum power point tracking controlof IDB converter supplied PV system. IEE Proceedings - Electric Power Applications. 148(6). 494–502. 111 indexed citations
16.
Senjyu, Tomonobu, et al.. (2001). Sensorless vector control of synchronous reluctance motors with disturbance torque observer. IEEE Transactions on Industrial Electronics. 48(2). 402–407. 44 indexed citations
17.
Senjyu, Tomonobu, et al.. (1999). Improvement of multi-machine power system stability by variable series capacitor (VSrC). IEEE Power Engineering Society. 1999 Winter Meeting (Cat. No.99CH36233). 114 b. 628–633 vol.1. 1 indexed citations
18.
Senjyu, Tomonobu, et al.. (1998). ROBUST CURRENT CONTROL METHOD OF VOLTAGE SOURCE PWM INVERTER. Electric Machines & Power Systems. 26(9). 977–988. 1 indexed citations
19.
Senjyu, Tomonobu, et al.. (1996). Rotor Oscillation Damping for Stepping Motors by Inverse Phase Excitation with Fuzzy Reasoning.. IEEJ Transactions on Industry Applications. 116(12). 1238–1245. 2 indexed citations
20.
Uezato, K. & Minoru Ueda. (1983). EFFECT OF PARAMETER CHANGES ON THE PERFORMANCE OF SOLID ROTOR THREE-PHASE RELUCTANCE MOTORS. Electric Machines & Power Systems. 8(3). 185–197. 2 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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