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Applications of IF Rough Relational Model to Deal with Diabetic Patients

  • Conference paper
Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8170))

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Abstract

This paper presents an intuitionistic fuzzy (IF) rough relational database model. The IF rough relational database model extends the IF and rough relational database models along with an IF rough relational algebra for querying. The usefulness of this model was illustrated with the Diabetic patients of Tripura where the various types of uncertainties are presented. For this study, first we design our database with an IF rough E-R diagram, created our database schema using an IF rough data definition and manipulation language (DDL and DML). Using IF Rough SQL-like languages, we then illustrate how the IF rough relational database may be queried and how the results are better than those of conventional databases.

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Author information

Authors and Affiliations

  1. Research Scholar, Tripura University, India

    Chhaya Gangwal

  2. Mathematics, UGC, India

    Rabi Nanda Bhaumik

  3. Biostatistics, Department of Community Medicine, Agartala Government Medical College, Agartala, Tripura

    Shishir Kumar

Authors
  1. Chhaya Gangwal
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  2. Rabi Nanda Bhaumik
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  3. Shishir Kumar
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Editor information

Editors and Affiliations

  1. University of Milano-Bicocca, viale Sarca 336/14, 20126, Milano, Italy

    Davide Ciucci

  2. Osaka University, 560-8531, Toyonaka, Osaka, Japan

    Masahiro Inuiguchi

  3. University of Regina, S4S 0A2, Regina, SK, Canada

    Yiyu Yao

  4. University of Warsaw, ul. Banacha, 2, 02-097, Warsaw, Poland

    Dominik Ślęzak

  5. Chongqing Institute of Green and Intelligent Technology, CAS, 401122, Chongqing, China

    Guoyin Wang

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© 2013 Springer-Verlag Berlin Heidelberg

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Gangwal, C., Bhaumik, R.N., Kumar, S. (2013). Applications of IF Rough Relational Model to Deal with Diabetic Patients. In: Ciucci, D., Inuiguchi, M., Yao, Y., Ślęzak, D., Wang, G. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2013. Lecture Notes in Computer Science(), vol 8170. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41218-9_20

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  • DOI: https://doi.org/10.1007/978-3-642-41218-9_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41217-2

  • Online ISBN: 978-3-642-41218-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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