Design of Intelligent Test Paper Generation System for Online Psychological Testing Based on Ant Colony Algorithm

In the calculation process of ant colony algorithm, the ant colony transfer is guided by the pheromone intensity and distance of each path, and the path of ant colony movement always tends to the path with the strongest information. Due to the influence of pheromone concentration, the subsequent ants have a higher probability of choosing a shorter path, thus forming a positive feedback mechanism, and eventually the entire ant colony will find an optimal path to find food sources. Intelligent paper grouping problem is actually a process of combinatorial optimization of the target according to the given constraints, so as to obtain the best solution. The traditional psychological test has many problems such as single test question, low test frequency and disclosure of personal privacy, so the results of psychological test are often not authentic. The network psychological test database is constructed, and the paper is automatically assembled based on ant colony algorithm. The convergence speed is fast, the robustness is outstanding, and it is convenient to realize the global algorithm.