Fuzzy Model of NP-Hard Problem: Uncertainty Causes for Identifying Best Goalkeepers

Abstract

Computational issues have been sorted in feasible, to some extent resolvable and unsolvable. Classes including P, NP, NP-complete and NP-Hard are utilized to group the given issue in light of intricacy of the issue. As of late numerous issues have been demonstrated to be NP-Hard in the space of different games particularly football match-up. Obviously we have found that recognizing best goalkeepers' concern has been neglected. In this issue, "Distinguishing best goalkeepers" from a bunch of players is troublesome and testing. Bit by bit numerical plan have been consolidated for the said NP difficult issue mathematically. Fuzzy models or fuzzy sets are numerical method for addressing dubiousness and uncertain data (consequently the term fuzzy). These models have the capacity of perceiving, addressing, controlling, deciphering, and utilizing information and data that are ambiguous and need assurance. Here authors have emphasized on identifying causes of uncertainty in order to find out best goalkeepers from the data set. Have validated four different parameters including linguistics terms, overlapping in the distribution of rules, parameter conversion to the triangular membership function and optimized rules. Proposed method have achieved to reduce 88% uncertainty with the help of rule optimization by setting up the experiment in the Fuzzy Inference System (FIS) under Mamdani Method.