A REVIEW-DENSITY BASED CLUSTERING ANALYSIS USING NEURAL NETWORK

Authors

  • Poonam Malik Research Scholar, JIET, Jind
  • Kirti Gautam Assistant Professor, JIET, JIND,

Keywords:

radio-frequency identification, meteorology, physics simulations, biology

Abstract

Analysis of data sets can find new correlations to spot business trends, prevent diseases, combat crime and so on. Scientists, business executives, practitioners of medicine, advertising and governments alike regularly meet difficulties with large data sets in areas including Internet search, finance and business informatics. Scientists encounter limitations in e-Science work, including meteorology, genomics, connectomics, complex physics simulations, biology and environmental research. Data sets are growing rapidly in part because they are increasingly gathered by cheap and numerous information-sensing mobile devices, aerial (remote sensing), software logs, cameras, microphones, radio-frequency identification (RFID) readers and wireless sensor networks.

References

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Navjot Kaur, Jaspreet Kaur Sahiwal, Navneet Kaur (2012) wrote on Efficient K-Means Clustering Algorithm Using Ranking Method In Data Mining

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Waldemar Wójcik & Konrad Gromaszek in 2014 (Lublin University of Technology, Poland) introduced “Data Mining Industrial Applications”.

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Published

31-03-2017

How to Cite

Poonam Malik, & Kirti Gautam. (2017). A REVIEW-DENSITY BASED CLUSTERING ANALYSIS USING NEURAL NETWORK. International Journal for Research Publication and Seminar, 8(1), 36–41. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/975

Issue

Vol. 8 No. 1 (2017): Jan - Mar 2017

Section

Original Research Article

License

Copyright (c) 2017 International Journal for Research Publication and Seminar

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