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Best Scientists - Electronics and Electrical Engineering
Takashi Hiyama

Takashi Hiyama

Kumamoto University
Japan

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Electronics and Electrical Engineering D-index 34 Citations 6,096 243 World Ranking 3859 National Ranking 157

Overview

What is he best known for?

The fields of study Takashi Hiyama is best known for:

Photovoltaic system
Wind power
Renewable energy

His work in Weibull distribution covers topics such as Statistics which are related to areas like Kurtosis. With his scientific publications, his incorporates both Kurtosis and Statistics. He is investigating Control (management) as part of his Control theory (sociology) and Model predictive control and Control (management) study. His research links Control (management) with Control theory (sociology). His Solar irradiance study overlaps with Meteorology and Irradiance. Takashi Hiyama conducts interdisciplinary study in the fields of Meteorology and Solar irradiance through his works. Many of his studies involve connections with topics such as Model predictive control and Artificial intelligence. Takashi Hiyama combines topics linked to Electric power system with his work on Power (physics). He connects Electrical engineering with Automotive engineering in his research.

His most cited work include:

Predicting remaining useful life of rotating machinery based artificial neural network (182 citations)
Robust decentralised PI based LFC design for time delay power systems (150 citations)
Model predictive based load frequency control_design concerning wind turbines (130 citations)

What are the main themes of his work throughout his whole career to date

His Radiology research incorporates a variety of disciplines, including Nuclear medicine and Internal medicine. Takashi Hiyama merges Internal medicine with Radiology in his study. Takashi Hiyama merges Artificial intelligence with Machine learning in his study. In his study, he carries out multidisciplinary Machine learning and Artificial intelligence research. Takashi Hiyama regularly ties together related areas like Wind power in his Electrical engineering studies. Power (physics) is often connected to Electric power system in his work. His Electric power system study often links to related topics such as Power (physics). His Quantum mechanics study frequently draws parallels with other fields, such as Voltage. He combines topics linked to Quantum mechanics with his work on Voltage.

Takashi Hiyama most often published in these fields:

Artificial intelligence (51.92%)
Electrical engineering (44.23%)
Power (physics) (42.31%)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Neural network based estimation of maximum power generation from PV module using environmental information

T. Hiyama;K. Kitabayashi.
IEEE Transactions on Energy Conversion (1997)

446 Citations

Identification of optimal operating point of PV modules using neural network for real time maximum power tracking control

T. Hiyama;S. Kouzuma;T. Imakubo.
IEEE Transactions on Energy Conversion (1995)

400 Citations

Intelligent Automatic Generation Control

Hassan Bevrani;Takashi Hiyama.
(2011)

385 Citations

Artificial neural network-polar coordinated fuzzy controller based maximum power point tracking control under partially shaded conditions

Syafaruddin;E. Karatepe;T. Hiyama.
Iet Renewable Power Generation (2009)

316 Citations

Predicting remaining useful life of rotating machinery based artificial neural network

Abd Kadir Mahamad;Sharifah Saon;Takashi Hiyama.
Computers & Mathematics With Applications (2010)

245 Citations

Decentralized model predictive based load frequency control in an interconnected power system

T.H. Mohamed;H. Bevrani;A.A. Hassan;T. Hiyama.
Energy Conversion and Management (2011)

244 Citations

Evaluation of neural network based real time maximum power tracking controller for PV system

T. Hiyama;S. Kouzuma;T. Imakubo;T.H. Ortmeyer.
IEEE Transactions on Energy Conversion (1995)

226 Citations

Robust decentralised PI based LFC design for time delay power systems

Hassan Bevrani;Takashi Hiyama.
Energy Conversion and Management (2008)

179 Citations

On Load–Frequency Regulation With Time Delays: Design and Real-Time Implementation

H. Bevrani;T. Hiyama.
IEEE Transactions on Energy Conversion (2009)

168 Citations

Model predictive based load frequency control_design concerning wind turbines

Tarek Hassan Mohamed;Jorge Morel;Hassan Bevrani;Takashi Hiyama.
International Journal of Electrical Power & Energy Systems (2012)

162 Citations

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Frequent Co-Authors

External Links

Personal Website for Takashi Hiyama