Design of an Online Sharing System for Ancient Literature Based on Mobile Technology

Abstract

At present, the study of ancient literature is gradually gaining attention but related knowledge still mostly exists offline without enough sharing online. In order to design an online sharing platform for ancient literature, an improved particle swarm optimization algorithm is used to form AAD-MOPSO based on cognitive radio architecture and multiple input multiple output and adaptive angular region partitioning. The improved algorithm is capable of adaptively and reasonably partitioning the channel in complex situations and avoiding the problem of local optimal solutions and over convergence, ensuring the balance of the number of particles in each region by angular partitioning, and balancing the population optimal solution and global optimal solution among each user target. In the simulation experiments, the sample targets are divided into two data sets equally and randomly, and each data set is divided into five groups and the test results and statistical averaging results of each group are recorded, and four other algorithms, namely PSO, MOPSO, logistics and K-means, are used for comparison. The experimental results show that the average accuracy rate of AAD-MOPSO algorithm is 88.05%, the average adaptation rate is 53.41%, and the average F1 value is 1.082, which are significantly higher than the other four algorithms, verifying the feasibility of the improved algorithm.