World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
38
Citations
6993
World Ranking
4855
National Ranking
196

Overview

Katsumi Uezato is affiliated with the University of the Ryukyus in Japan. Their academic career is primarily associated with this institution.

There is no available detailed information on their recent papers, frequent co-authors, publication venues, book publications, main fields or subfields of study, or specific topics of work.

No awards or distinctions have been recorded in the available data. There is no indication that Katsumi Uezato is deceased.

The profile is limited to basic biographical and institutional affiliation details due to the absence of publications or other academic contributions in the provided information.

Best Publications

  • Neural-network-based maximum-power-point tracking of coupled-inductor interleaved-boost-converter-supplied PV system using fuzzy controller

    M. Veerachary;T. Senjyu;K. Uezato

  • A fast technique for unit commitment problem by extended priority list

    T. Senjyu;K. Shimabukuro;K. Uezato;T. Funabashi

  • One-Hour-Ahead Load Forecasting Using Neural Networks

    T. Senjyu;H. Takara;K. Uezato;T. Funabashi

  • A hybrid power system using alternative energy facilities in isolated island

    T. Senjyu;T. Nakaji;K. Uezato;T. Funabashi

  • Voltage-based maximum power point tracking control of PV system

    M. Veerachary;T. Senjyu;K. Uezato

  • An adaptive dead-time compensation strategy for voltage source inverter fed motor drives

    N. Urasaki;T. Senjyu;K. Uezato;T. Funabashi

  • Adaptive Dead-Time Compensation Strategy for Permanent Magnet Synchronous Motor Drive

    N. Urasaki;T. Senjyu;K. Uezato;T. Funabashi

  • A unit commitment problem by using genetic algorithm based on unit characteristic classification

    T. Senjyu;H. Yamashiro;K. Uezato;T. Funabashi

  • Feedforward maximum power point tracking of PV systems using fuzzy controller

    M. Veerachary;T. Senjyu;K. Uezato

  • Maximum power point tracking control of IDB converter supplied PV system

    M. Veerachary;T. Senjyu;K. Uezato

  • Next day load curve forecasting using hybrid correction method

    T. Senjyu;P. Mandal;K. Uezato;T. Funabashi

  • A novel calculation method for iron loss resistance suitable in modeling permanent-magnet synchronous motors

    N. Urasaki;T. Senjyu;K. Uezato

  • Maximum power point tracking of coupled inductor interleaved boost converter supplied PV system

    M. Veerachary;T. Senjyu;K. Uezato

  • Wind velocity and rotor position sensorless maximum power point tracking control for wind generation system

    Tomonobu Senjyu;Satoshi Tamaki;Endusa Muhando;Naomitsu Urasaki

  • Position control of ultrasonic motors using MRAC and dead-zone compensation with fuzzy inference

    T. Senjyu;T. Kashiwagi;K. Uezato

  • Output power control of wind turbine generator by pitch angle control using minimum variance control

    Tomonobu Senjyu;Ryosei Sakamoto;Naomitsu Urasaki;Hiroki Higa

  • Speed control of ultrasonic motors using neural network

    T. Senjyu;H. Miyazato;S. Yokoda;K. Uezato

  • Next day load curve forecasting using recurrent neural network structure

    T. Senjyu;P. Mandal;K. Uezato;T. Funabashi

  • Relationship of parallel model and series model for permanent magnet synchronous motors taking iron loss into account

    N. Urasaki;T. Senjyu;K. Uezato

  • Future load curve shaping based on similarity using fuzzy logic approach

    T. Senjyu;S. Higa;K. Uezato

Frequent Co-Authors

Tomonobu Senjyu
Tomonobu Senjyu University of the Ryukyus
Toshihisa Funabashi
Toshihisa Funabashi University of the Ryukyus
Naomitsu Urasaki
Naomitsu Urasaki University of the Ryukyus
Sanjib Kumar Panda
Sanjib Kumar Panda National University of Singapore
Marta Molinas
Marta Molinas Norwegian University of Science and Technology

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Best Scientists Citing Katsumi Uezato