Football predictions based on a fuzzy model with genetic and neural tuning
AP Rotshtein, M Posner, AB Rakityanskaya - Cybernetics and Systems …, 2005 - Springer
AP Rotshtein, M Posner, AB Rakityanskaya
Cybernetics and Systems Analysis, 2005•SpringerA 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.
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.
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.
Springer
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