Hybrid Neural Network Based Risk Assessment Method for Large Scale Sports Events

Abstract

This paper focuses on the problem of risk assessment method for large scale sports events which is an important problem in modern sports management. The index system for large scale sports events risk assessment is proposed in advance, which is made up of three categories: 1) risk before match, 2) risk in match and 3) risk after match. Particularly, eighteen influencing factors are design which can cover all aspects of the large scale sports events risk assessment. Structure of the hybrid neural network is contructed by three layers, which are "the input layer", "the hidden layer", and "the output layer". Particularly, the output layers can compute the regression function values, and the regression function of the artificial neural network can be computed through a linear integration of some nonlinear basis functions. Afterwards, utilizing a training dataset and its updating version, values of the decision functions of the multi-class support vector classifier can be obtained by the regression functions based on the artificial neural network. Finally, experiments are conducted to test the effectiveness of our algorithm. The conclusions can be drawn that compared with the artificial neural network, the proposed hybrid neural network is more suitable for the risk assessment of large scale sports events.