Chenweiwen Liu and  Weilin Wang. Injury Risk Screening of Football Players Based on Ahp-Fuzzy Comprehensive Evaluation. Dynamic Systems and Applications 29 (2020) No. 5, 1842 – 1850

https://doi.org/10.46719/dsa202029516

ABSTRACT.
Various techniques have been used to create a system of financial projections. Specifically, the result of a football match prediction system, logistics systems, K-nearest neighbor (K-NN) and other technologies is delayed, has developed machine learning. Select any field of technology depends on the feature set of applications. The computer developer and designer of the first task, in most cases, is to obtain high prediction accuracy. Suppose the kernel compared to previous experiments proposed shown to have better injury. Also, we contacted the team to incorporate techniques for dealing with the indefinite kernel to propose a new kernel. The purpose of this research is to study the Fuzzy Comprehensive Evaluation(FCV) to the predictive Injury of a soccer match in football. A combination of Gaussian kernel types is used in 10,000 repetitions to generate 65 Correlation vectors. Twelve examples are trained to predict the outcome of a football match (data set) and ten matches. The research results show 60.3%, which is a relatively low prediction accuracy. Until confirmed by other studies, the FCV-based system (designed here) is sufficient in this application domain.

Keywords: Kernel Function Combined, machine learning, prediction system, vector machine Correlation