Table of Contents Author Guidelines Submit a Manuscript
Applied Computational Intelligence and Soft Computing
Volume 2013, Article ID 265924, 7 pages
Research Article

Fuzzy Environmental Model for Evaluating Water Quality of Sangam Zone during Maha Kumbh 2013

1Department of Mathematics, Motilal Nehru National Institute of Technology, Allahabad, Uttar Pradesh 211004, India
2Department of Mathematics, Dayanand College of Commerce, Latur, Maharashtra 413512, India

Received 25 May 2013; Accepted 8 July 2013

Academic Editor: Baoding Liu

Copyright © 2013 Pankaj Srivastava et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. C. Meyer, Evaluating Water Quality Using Spatial Interpolation Methods, Pinellas Country, Florida, USA, 2006.
  2. N. B. Harmancioglu, Y. Icaga, and A. Gul, “The use of an optimization method in assessment of water quality sampling sites,” European Water Resource Association Journal, vol. 5, no. No6, pp. 25–34, 2004. View at Google Scholar
  3. K. Le. Rosemary, C. Rackauckas, and N. Ulloa, “Assessment of statistical methods for water quality monitoring in Marylands tidal waterways,” SIAM Undergraduate Research, pp. 22–41.
  4. L. A. Zadeh, “Fuzzy sets,” Information and Control, vol. 8, no. 3, pp. 338–353, 1965. View at Google Scholar · View at Scopus
  5. R. Jain, “Decision making in the presence of fuzzy variables,” IEEE Transactions on Systems, Man and Cybernetics, vol. 6, no. 10, pp. 698–703, 1976. View at Publisher · View at Google Scholar · View at Scopus
  6. R. E. Bellman and L. A. Zadeh, “Decision making in a fuzzy environment, Management Science,” Management Science, vol. 17, no. 4, pp. B141–B164, 1970. View at Google Scholar · View at Scopus
  7. S. Cho, O. K. Ersoy, and M. Lehto, “An algorithm to compute the degree of match in fuzzy systems,” Fuzzy Sets and Systems, vol. 49, no. 3, pp. 285–299, 1992. View at Google Scholar · View at Scopus
  8. M. Kumar, Application of Fuzzy Theory Approach to Study Water Pollution of Sangam Zone, M.Tech. Thesis Civil Engineering, Motilal Nehru National Institute of Technology, Allahabad, India, 2004.
  9. S. Yadav, Water quality assesment of water Ganga and Yamuna during Ardh Kumbh-2007 by Fuzzy Analysis [M.S. thesis], Environment Science, Allahabad University, 2007.
  10. D. Pandey, V. Mahajan, and P. Srivastava, “Rule-based system for cardiac analysis,” National Academy Science Letters, vol. 29, no. 7-8, pp. 299–309, 2006. View at Google Scholar · View at Scopus
  11. P. Srivastava and A. Srivastava, “A note on soft computing approach for cardiac analysis,” Journal of Basic and Applied Scientific Research, vol. 2, no. 1, pp. 376–385, 2012. View at Google Scholar
  12. P. Srivastava and A. Srivastava, “Spectrum of soft computing risk assessment scheme for hypertension,” International Journal of Computer Applications, vol. 44, no. 17, pp. 23–30, 2012. View at Google Scholar
  13. P. Srivastava and N. Sharma, “A spectrum of soft computing model for medical diagnosis,” Applied Mathematics and Information Sciences. In press.
  14. P. Srivastava, A. Srivastava, and R. Sirohi, “Soft computing tools and classification criterion for hepatitis B,” International Journal of Research and Reviews in Soft & Intelligent Computing, vol. 2, no. 2, 2012. View at Google Scholar
  15. P. Srivastava, N. Sharma, and R. Singh, “Soft computing diagnostic system for diabetes,” International Journal of Computer Applications, vol. 47, no. 18, pp. 22–27, 2012. View at Google Scholar
  16. E. Sanchez, “Medical diagnosis and composite fuzzy relations,” in Advances in Fuzzy Set Theory and Application, M. M. Gupta, R. K. Ragade, and R. R. Yager, Eds., pp. 437–444, North Holland, Amsterdam, Netherlands, 1979. View at Google Scholar
  17. A. P. Rotshtein, M. Posner, and H. B. Rakytyanska, “Cause and effect analysis by fuzzy relational equations and a genetic algorithm,” in Proceedings of International Conference on Fuzzy Logic and Its Application (FUZZY '97), pp. 125–130, 1997.
  18. L. A. Zadeh, The Concept of Linguistic Variable and Its Application to Approximate Decision Making, Mir, Moscow, Russia, 1976.
  19. A. Rotshtein, “Modication of Saaty method for the construction of fuzzy set membership functions,” Reliability Engineering and System Safety, vol. 91, pp. 1095–1101, 1997. View at Google Scholar