Improvement of culture media efficiency in Internet of Things based on global numerical ant colony algorithm

Abstract

Exploring the cultural media under the Internet of Things is not only an inevitable need to understand the cultural landscape of the Internet of Things era, but also an extension of the people themselves in the new medium. Understanding the Internet of Things as a new paradigm of media organization and production, it should clarify the technology and body in the Internet of Things, so it can clarify the objective for a relationship with the media. The Internet of Things solves the virtual interdimensional problem of information dissemination and social interaction, opening up a new vision of cultural communication. However, the Internet of Things technology makes the ideological and cultural communication channels more diverse and more complex. How to improve the efficiency of cultural media is the hotspot of current research. Therefore, this article takes cultural media as the research object and adopts the Internet of Things technology to construct the IoT culture media efficiency optimization model of the global numerical ant colony algorithm. Firstly, the population space and belief space of the cultural algorithm are redesigned by using the new bi-level evolutionary mechanism. Then, the maximum and minimum ant colony system is used to construct the population space, and the current optimal solution is improved by the 3-opt cross-transform operation in the belief space. Finally, the simulation experiments are set up to verify the effectiveness of the proposed algorithm. The experimental results show that the global numerical ant colony algorithm based on the Internet of Things is better than the traditional ant colony algorithm and the cultural ant colony algorithm, and the convergence speed is faster, which further improves the efficiency of the cultural media.