What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Algorithm
His main research concerns Control theory, Artificial neural network, Nonlinear system, Artificial intelligence and Algorithm.
His studies deal with areas such as Active noise control, Noise, Electric power system and Control engineering as well as Control theory.
Ganapati Panda works mostly in the field of Artificial neural network, limiting it down to topics relating to Power-system protection and, in certain cases, Noise, Polynomial kernel, Static VAR compensator, Kernel method and Support vector machine.
His work deals with themes such as Full state feedback, Estimation theory and Multilayer perceptron, which intersect with Nonlinear system.
His Artificial intelligence study combines topics in areas such as Machine learning and Pattern recognition.
His Algorithm study integrates concerns from other disciplines, such as Discrete wavelet transform, Wavelet transform, Theoretical computer science and Signal processing.
His most cited work include:
- Identification of nonlinear dynamic systems using functional link artificial neural networks (326 citations)
- Power quality analysis using S-transform (313 citations)
- A survey on nature inspired metaheuristic algorithms for partitional clustering (284 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Artificial intelligence, Algorithm, Control theory, Artificial neural network and Mathematical optimization.
He interconnects Machine learning and Pattern recognition in the investigation of issues within Artificial intelligence.
The Algorithm study which covers Signal processing that intersects with Noise.
His studies in Control theory integrate themes in fields like Active noise control, Noise and Electronic engineering.
His Electronic engineering research integrates issues from Fault and S transform.
His Particle swarm optimization research is multidisciplinary, incorporating perspectives in Evolutionary computation and Swarm behaviour.
He most often published in these fields:
- Artificial intelligence (30.10%)
- Algorithm (28.72%)
- Control theory (21.45%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (30.10%)
- Pattern recognition (15.92%)
- Algorithm (28.72%)
In recent papers he was focusing on the following fields of study:
Ganapati Panda mainly investigates Artificial intelligence, Pattern recognition, Algorithm, Adaptive filter and Speech recognition.
Artificial intelligence and Computer vision are commonly linked in his work.
He has included themes like DBSCAN, Similarity measure and Cluster analysis in his Algorithm study.
His Adaptive filter research is included under the broader classification of Control theory.
His biological study spans a wide range of topics, including Filter and Filter.
In Residual, Ganapati Panda works on issues like Artificial neural network, which are connected to Range.
Between 2014 and 2021, his most popular works were:
- Sentiment analysis of Twitter data for predicting stock market movements (99 citations)
- Design of computationally efficient density-based clustering algorithms (28 citations)
- Design of computationally efficient density-based clustering algorithms (28 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Algorithm
Artificial intelligence, Algorithm, Particle swarm optimization, Pattern recognition and Computer vision are his primary areas of study.
His work on Feature extraction, Matching and Segmentation as part of his general Artificial intelligence study is frequently connected to Fundus and Glaucoma, thereby bridging the divide between different branches of science.
The study incorporates disciplines such as OPTICS algorithm, Data mining and SUBCLU in addition to Algorithm.
His Particle swarm optimization study incorporates themes from Active noise control and Transfer function.
Ganapati Panda works mostly in the field of Pattern recognition, limiting it down to concerns involving Speech recognition and, occasionally, Image, Feature, Numeral system and MNIST database.
His research integrates issues of Control theory and Nonlinear system in his study of Filter bank.
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