Cluster Based Analysis and Consumption of Food Products in Targeted Public Distribution System
Keywords:
K-means, K-harmonic means, PDS, cluster based PDS
Abstract
The Public Distribution System in India is 50 years old. At present it is being carried on as an anti-inflationary and antipoverty system. Tamil Nadu, the southernmost State in the country, is adopting the Universal Public Distribution System covering its entire population and supplying regularly rice, wheat, sugar, kerosene and other products like pulses, edible oil etc. The PDS is a centrally sponsored scheme that entitles beneficiaries to subsidized food grains every month. Several challenges have been identified in the implementation of PDS like (i) Targeting errors (ii) Large leakages or diversion (iii) The elimination of bogus cards and (iv) The problems in Fair Price Shops. This paper analyses and evaluates the problems and finds the possible solutions using the data mining techniques based on preprocessing and clustering. The K-means and K-harmonic means algorithms are combined to cluster the data based on the type of food commodities for rice and wheat.
Downloads
- Article PDF
- TEI XML Kaleidoscope (download in zip)* (Beta by AI)
- Lens* NISO JATS XML (Beta by AI)
- HTML Kaleidoscope* (Beta by AI)
- DBK XML Kaleidoscope (download in zip)* (Beta by AI)
- LaTeX pdf Kaleidoscope* (Beta by AI)
- EPUB Kaleidoscope* (Beta by AI)
- MD Kaleidoscope* (Beta by AI)
- FO Kaleidoscope* (Beta by AI)
- BIB Kaleidoscope* (Beta by AI)
- LaTeX Kaleidoscope* (Beta by AI)
How to Cite
Published
2013-03-15
Issue
Section
License
Copyright (c) 2013 Authors and Global Journals Private Limited
This work is licensed under a Creative Commons Attribution 4.0 International License.