Bijaya Ketan Panigrahi mainly investigates Artificial intelligence, Mathematical optimization, Particle swarm optimization, Algorithm and Wavelet transform. The concepts of his Artificial intelligence study are interwoven with issues in Swarm intelligence, Machine learning and Pattern recognition. His biological study spans a wide range of topics, including Economic dispatch and Robustness.
His Particle swarm optimization research includes themes of Electricity, Motion planning and Fuzzy logic. His Algorithm study deals with Electric power system intersecting with Traffic congestion and Smart grid. Wavelet covers he research in Wavelet transform.
His scientific interests lie mostly in Artificial intelligence, Mathematical optimization, Control theory, Electric power system and Pattern recognition. His research on Artificial intelligence frequently links to adjacent areas such as Machine learning. Mathematical optimization is closely attributed to Algorithm in his work.
His Control theory research includes elements of Power factor, Fault, Photovoltaic system and AC power. Bijaya Ketan Panigrahi focuses mostly in the field of Electric power system, narrowing it down to matters related to Relay and, in some cases, Overcurrent. In general Pattern recognition, his work in Segmentation is often linked to Probabilistic neural network linking many areas of study.
His primary scientific interests are in Control theory, Artificial intelligence, Photovoltaic system, Pattern recognition and Control theory. Bijaya Ketan Panigrahi has included themes like Power factor, AC power, Integrator, Boost converter and Microgrid in his Control theory study. Artificial intelligence is frequently linked to Computer vision in his study.
His research in Photovoltaic system intersects with topics in Maximum power point tracking, Voltage source and Topology. Bijaya Ketan Panigrahi combines subjects such as Artificial neural network, Robustness and Transfer of learning with his study of Pattern recognition. His Convolutional neural network research incorporates themes from Overhead, MNIST database, Algorithm, Particle swarm optimization and Swarm behaviour.
His primary areas of study are Photovoltaic system, Artificial intelligence, Power factor, Control theory and Pattern recognition. His studies deal with areas such as Statistics and Identification as well as Artificial intelligence. His study in Power factor is interdisciplinary in nature, drawing from both Maximum power point tracking, Control theory, Harmonics, AC power and Voltage source.
His work on Convolutional neural network is typically connected to Abnormality as part of general Pattern recognition study, connecting several disciplines of science. He interconnects Artificial neural network, Extreme learning machine, Support vector machine, Feature selection and Robustness in the investigation of issues within Convolutional neural network. His studies in Artificial neural network integrate themes in fields like Mathematical optimization and Regression.
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Power quality analysis using S-transform
P. E. K. Dash;B. K. Panigrahi;G. Panda.
IEEE Power & Energy Magazine (2002)
Detection and Classification of Power Quality Disturbances Using S-Transform and Probabilistic Neural Network
S. Mishra;C.N. Bhende;B.K. Panigrahi.
IEEE Transactions on Power Delivery (2008)
Adaptive particle swarm optimization approach for static and dynamic economic load dispatch
B.K. Panigrahi;V. Ravikumar Pandi;Sanjoy Das.
Energy Conversion and Management (2008)
Multiobjective Particle Swarm Algorithm With Fuzzy Clustering for Electrical Power Dispatch
S. Agrawal;B.K. Panigrahi;M.K. Tiwari.
IEEE Transactions on Evolutionary Computation (2008)
Bacterial foraging optimisation: Nelder-Mead hybrid algorithm for economic load dispatch
B.K. Panigrahi;V. Ravikumar Pandi.
Iet Generation Transmission & Distribution (2008)
Exploratory Power of the Harmony Search Algorithm: Analysis and Improvements for Global Numerical Optimization
S Das;A Mukhopadhyay;A Roy;A Abraham.
systems man and cybernetics (2011)
Power Quality Disturbance Classification Using Fuzzy C-Means Algorithm and Adaptive Particle Swarm Optimization
B. Biswal;P.K. Dash;B.K. Panigrahi.
IEEE Transactions on Industrial Electronics (2009)
A clonal algorithm to solve economic load dispatch
B.K. Panigrahi;Salik R. Yadav;Shubham Agrawal;M.K. Tiwari.
Electric Power Systems Research (2007)
Optimal coordination of directional over-current relays using Teaching Learning-Based Optimization (TLBO) algorithm
Manohar Singh;B.K. Panigrahi;A.R. Abhyankar.
International Journal of Electrical Power & Energy Systems (2013)
Handbook of Swarm Intelligence: Concepts, Principles and Applications
Bijaya Ketan Panigrahi;Yuhui Shi;Meng-Hiot Lim.
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