Mobile group intelligence aware network log information collection based on Markov prediction

Abstract

Aiming at the problems of low completion rate and large remaining proportion of collection tasks in traditional information collection methods, the Markov prediction model of multi sensing location is used to dynamically collect the real-time information of mobile group intelligence sensing network logs. The trajectory sequence generation algorithm was used to extract the trajectory sequence of mobile users. Using the multi perception complementary control method, the learning transition probability matrix was obtained. Adopting improved methods could effectively improve the proportion of task completion. By describing the problem, the Markov prediction model of multi sensing location was introduced, the detailed prediction steps were given, and the information was collected dynamically. The experimental results show that the task completion rate of the improved method in this paper is about 93.24%, and the highest remaining proportion is 96.84%.

Keywords

• markov prediction model
• mobile group intelligence perception network
• log information
• information collection
• multi perception location