Sports Event Level Measurement Indicator System Using Multisensor Information Fusion

Abstract

In view of the imperfection of the measurement index of the level of sports events, the coverage rate of the measurement index is low and the stability is poor. Therefore, this paper puts forward a sports event level measurement index system based on multisensor information fusion. First, the simulated annealing algorithm is used to cluster the grouped sensors and fuse the optimal Bayesian estimation of compatible sensors. Second, the relative entropy measure method is used to expand the compatibility measure of the sensor information in the group, and the optimal Bayesian estimation value of the consistent measure test is obtained. The outliers are eliminated, the optimal fusion value is obtained by the overall weighted statistical fusion, and the alternative measure index system is constructed. Finally, analytic hierarchy process (AHP) is used to calculate the weight of each alternative index, so as to achieve the final measurement index. The results show that the standard deviation of clustering average energy consumption is low, and the energy loss is small. The system can effectively construct the measurement index, and the index coverage rate is as high as 95%.

Information Extraction and Spatial Pattern Analysis of Sports Events Based on Deep Learning

“…More and more people take part in sports, enjoy sports, and pay much attention to information of sports events [1][2][3][4]. All sorts of sports event information are delivered via information communication media, such as sports newspapers, sports television channels, sports websites, and sports new media [5][6][7][8][9][10]. e analysis of sports event information can disclose the public's concern over di erent types of sports events, re ect the spatial pattern of sports event information, and guide the organization of such events [11][12][13][14][15][16].…”