Forecasting of Cotton Yield with Fuzzy Information

  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract

    The models of cotton yield forecasting using methods of fuzzy mathematics are considered. In the paper, the economic system as a human-centered, realistic multiagent system characterized by incompleteness and partial reliability of information is considered. Representation of the behavior of economic agents in our approach is based on fuzzy logic and is given by inaccurate constraints.



  • Keywords

    multiagent system, fuzzy approach, cotton yield, membership function.

  • References

      [1] Sattorov D. Variety, soil, fertilizer and crop. - Tashkent. Mehnat. (1988).

      [2] Orlovsky S.A. Decision problems with fuzzy source information. Мoscow: the Science, (1981).

      [3] Mukhamedieva D.T. Building hybrid systems for monitoring and decision making. Publishing house "Palmarium Academic Publishing". AV Akademikerverlag GmbH & Co.KG Heinrich-Böcking-Str. 6-8, 66121 Saarbrucken, Germany317 p.. (2017).

      [4] Mukhamedieva D.T. Intellectual analysis of fuzzy solutions to incorrect problems Palmarium Academic Publishing. AV Akademikerverlag GmbH & Co.KG Heinrich-Böcking-Str. 6-8, 66121 Saarbrucken, Germany. 327 p.(2017).

      [5] Muhamediyeva D.T., Safarova L. Creation of hybrid intelligent system for nonlinear relations identification // International Journal of Research in Engineering and Technology, Vol.6, №9, pp.18-23.(2017).

      [6] G.A. Akerlof. The missing motivation in macroeconomics. The American Economic Review, Vol.97, No.1, pp.5-36.(2007).

      [7] D. Romer. "Advanced Macroeconomics", Third Edition, McGraw-Hill/Irvin. New York, p.678.(2006).

      [8] J. M. Dowling, Y. Chin-Fang. "Modern Developments in Behavioral Economics. Social Science Perspectives on Choice and Decision making", World Scientific Publishing Co. Pte. Ltd. Singapore, p.446. (2007).

      [9] D. Kahneman, A. Tversky. Prospect theory: An analysis of decision under risk, Econometrica47. pp.263-291. (1979).




Article ID: 22065
DOI: 10.14419/ijet.v7i4.19.22065

Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.