Analysis of Syntactic Complexity and Semantic Coherence of Academic English Writing Based on Particle Swarm Optimization

Writing is an important part of testing language ability, and it urgent to find some objective indicators determine evaluate the surface structure, which will help learners’ better master target language. Complexity semantic coherence are considered be factor in teaching second writing. In practice, due complexity English writing syntax, such as a large number high-dimensional nonlinear optimization problems, new intelligent evaluation method needed solve them. At present, particle swarm (PSO) has been widely used function optimization, neural network training, combinatorial other fields. This paper studies syntactic academic based on PSO. The phrases related achievement. When experiments reaches 25, significant values data mining algorithm, artificial intelligence decision tree PSO algorithm 0.008, 0.003, 0.002, 0.013, respectively, shows that best among