His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Thresholding, Control theory and Cuckoo search. His studies in Artificial intelligence integrate themes in fields like Algorithm and Transmission line. His work in the fields of Pattern recognition, such as Discrete wavelet transform, overlaps with other areas such as Singular value.
His study explores the link between Thresholding and topics such as Image segmentation that cross with problems in Peak signal-to-noise ratio. His Control theory research incorporates themes from Power factor, Harmonics, Stator, Harmonic and Leakage inductance. Girish Kumar Singh has researched Cuckoo search in several fields, including Evolutionary algorithm and Differential evolution.
The scientist’s investigation covers issues in Control theory, Artificial intelligence, Algorithm, Pattern recognition and Prototype filter. His research in Control theory intersects with topics in Elliptic filter, Phase, Control engineering and Induction generator, Voltage. His research on Artificial intelligence often connects related topics like Computer vision.
His research integrates issues of Frequency response and Passband in his study of Algorithm. His Prototype filter research incorporates elements of Electronic engineering and Filter bank. As a part of the same scientific study, Girish Kumar Singh usually deals with the Electronic engineering, concentrating on Fault and frequently concerns with Electric power system.
His main research concerns Artificial intelligence, Pattern recognition, Algorithm, Control theory and Artificial neural network. His Artificial intelligence research is multidisciplinary, incorporating elements of Frequency domain and Identification. His Pattern recognition research is multidisciplinary, incorporating perspectives in Entropy and Image database.
The various areas that Girish Kumar Singh examines in his Algorithm study include Filter, Filter design and Thresholding. Girish Kumar Singh interconnects Phase, Reduction, Stability, Induction generator and Rotor in the investigation of issues within Control theory. His Artificial neural network research focuses on subjects like Fuzzy logic, which are linked to Histopathology, Magnification and Adaptive system.
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.
Solar power generation by PV (photovoltaic) technology: A review
Multi-phase induction machine drive research—a survey
Electric Power Systems Research (2002)
Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur's entropy
Ashish Kumar Bhandari;Vineet Kumar Singh;Anil Kumar;Girish Kumar Singh.
Expert Systems With Applications (2014)
Induction machine drive condition monitoring and diagnostic research—a survey
G.K Singh;Sa'ad Ahmed Saleh Al Kazzaz.
Electric Power Systems Research (2003)
Self-excited induction generator research—a survey
Electric Power Systems Research (2004)
A simple indirect field-oriented control scheme for multiphase induction machine
G.K. Singh;K. Nam;S.K. Lim.
IEEE Transactions on Industrial Electronics (2005)
Modified artificial bee colony based computationally efficient multilevel thresholding for satellite image segmentation using Kapur's, Otsu and Tsallis functions
A.K. Bhandari;A. Kumar;G.K. Singh.
Expert Systems With Applications (2015)
Feature Extraction using Normalized Difference Vegetation Index (NDVI): A Case Study of Jabalpur City
A.K. Bhandari;A. Kumar;G.K. Singh.
Procedia Technology (2012)
Power system harmonics research: a survey
G. K. Singh.
European Transactions on Electrical Power (2009)
A simple fuzzy logic based robust active power filter for harmonics minimization under random load variation
G.K. Singh;A.K. Singh;R. Mitra.
Electric Power Systems Research (2007)
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