Cybernetics and Systems Analysis

, Volume 41, Issue 4, pp 619–630

Football Predictions Based on a Fuzzy Model with Genetic and Neural Tuning

  • A. P. Rotshtein
  • M. Posner
  • A. B. Rakityanskaya
Article

DOI: 10.1007/s10559-005-0098-4

Cite this article as:
Rotshtein, A.P., Posner, M. & Rakityanskaya, A.B. Cybern Syst Anal (2005) 41: 619. doi:10.1007/s10559-005-0098-4

Abstract

A model is proposed for predicting the result of a football match from the previous results of both teams. This model underlies the method of identifying nonlinear dependencies by fuzzy knowledge bases. Acceptable simulation results can be obtained by tuning fuzzy rules using tournament data. The tuning procedure implies choosing the parameters of fuzzy-term membership functions and rule weights by a combination of genetic and neural optimization techniques.

Keywords

football match prediction fuzzy logic fuzzy knowledge bases genetic algorithm neural fuzzy network 

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Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  • A. P. Rotshtein
    • 1
  • M. Posner
    • 1
  • A. B. Rakityanskaya
    • 2
  1. 1.Jerusalem College of TechnologyMachon LevIsrael
  2. 2.Vinnitsa National Technical UniversityVinnitsaUkraine

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