Time Series Analysis of Oceanographic Data Using Clustering Algorithms

  • D. J. Santosh Kumar
  • S. P. Vighneshwar
  • Tusar Kanti Mishra
  • Satya V. Jampana
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 5)

Abstract

With the availability of huge data sets in device fields like finances to weather, it becomes very important to quality analysis and interprets the results. In such scenario K-Means and DBSCAN clustering algorithms are used for effective data grouping to get insight into the hidden structure in the data. In this paper focus on the application of clustering to ocean data observations. An attempt is made to correlate the resulting clusters to the variability focused during cyclones.

Keywords

Data mining Clustering Temperature Salinity Buoy Time series 

Notes

Acknowledgements

Authors from ANITS would like to thank HOD ANITS for support. Authors from INCOIS would like to thank the Director INCOIS for providing all necessary facilities to carry out this work.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  • D. J. Santosh Kumar
    • 1
  • S. P. Vighneshwar
    • 2
  • Tusar Kanti Mishra
    • 1
  • Satya V. Jampana
    • 2
  1. 1.Computer Science and Technology, Department of CSEANIL Neerukonda Institute of Technology and Sciences (ANITS)VisakhapatnamIndia
  2. 2.Indian National Centre for Ocean Information Services (INCOIS)HyderabadIndia

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