Allocation and Optimization of Public Sports Facilities Resources in International Tourist Cities Based on Fuzzy Multicriteria Decision-Making Algorithm

Abstract

With the improvement of the economic level and the continuous improvement of people living standards, international tourism has become a major boom. International tourism can not only improve the local economic income but also improve the construction of local facilities. Not only does the development of a country tourism depend on the local tourism attraction, but also the economic situation of country is more critical for tourism. The arrangement of sports facilities is also key to the popularity of international tourist cities and to increase tourism, because public sports facilities can not only enhance the physical exercise of tourists but also display local characteristics in the form of sports facilities. The decisions on public sports facilities are based on local government policies and other factors such as travelers preferences, which requires reference to the layout of public sports facilities in successful international tourist cities. This research uses fuzzy multicriteria decision-making algorithm and neural network technology to conduct decision-making and prediction research on the relevant factors of public sports resource allocation in international tourist cities. The research results show that the fuzzy multicriteria algorithm has high accuracy for decision-making and prediction of public sports resource setting. The maximum error of multicriteria algorithm and neural network method in predicting the relevant factors of public sports setting is only 2.45%, and this part of the error comes from the needs of tourists. The smallest error is only 1.34%. The fuzzy multicriteria algorithm has an accuracy of more than 95% for decision-making and prediction of public sports facilities, which is beneficial to decision makers of sports settings in international tourist cities.