Nature Inspired Clustering Algorithms For Analysis Of Natural Databases | 23760
Hydrology: Current Research
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Data Clustering concept started with K-means algorithm which was reported around 1957. After more than 50 years of its
existence the algorithm is still popular and widely used for partitioning large database. The 1990 kick started a revolution
in the area of clustering with the use of nature inspired meta-heuristics. The nature inspired techniques are also popularly
known as artificial intelligence (AI) mechanisms. With this a new set of algorithms like Genetic Algorithm, Particle Swarm
Optimization, Ant Colony Optimization, Differential Evolution, Artificial Immune Systems, Bacterial Foraging Optimization
are evolved which are being used for cluster analysis. The beauty of these algorithms are, they employ a set of naturally driven
particles (which represent potential solutions of a problem) to explore the search space and assure greater probability to achieve
global solutions. They overcome the local optima solutions by using collaborative learning, where the traditional derivative
based algorithms like K-means, K-nearest neighbor failed. Present research focus on the development of multi-objective and
constrained approaches in the nature inspired clustering. These set of complex algorithms have the potential to accurately
analyze databases derived from natural phenomenon like earthquakes, volcanic eruptions, and seismic sea waves like Tsunami.
Timely use of the derived results can able to save a mass population of a geographic region from the natural hazards.
Satyasai Jagannath Nanda has completed his PhD at the age of 28 years from School of Electrical Sciences, Indian Institute of Technology Bhubaneswar. Prior to
this he has received the MTech degree in Electronics and Communication Engineering from National Institute of Technology, Rourkela and BE from Biju Patnaik
University of Technology, Odisha. He is presently working as an Assistant Professor in the Department of Electronics and Communication Engg., MNIT Jaipur.
During the PhD he was awarded the GESP Research Fellowship by Dept. of Foreign Affairs and International Trade, Govt. of Canada in the Dept. of Earth Sciences,
University of Western Ontario, Canada. He has published 6 papers in international journals and 11 papers in the IEEE conference proceedings. Within a short time
span his papers have received 57 citations with H-index 5 and I-10 index 1. He has been serving as constant reviewer of IEEE transactions on Data and Knowledge
Engineering, Elsevier?s Swarm and Evolutionary Computation, Applied Soft Computing, Swarm and Evolutionary Computation, Information Sciences.
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