Research On Intelligent Test Paper Generating Strategy Based On Genetic Algorithm And BP Neural Network

摘要

The prevalence of MOOC (Massive Open Online Course), while providing us with a new efficient way of learning, demands an evolved online test system for certificating attended students properly. As examination of each course still being the simple and powerful way to check out, generating test paper as the core of exam system, is particularly important. Therefore, we present an enhanced method based on BP neural network optimizing the weight coefficient of objective function in paper generating model. After the Restructuring of mutation operator, and adjusting of crossover operator with the adaptive function, the performance of genetic algorithm modified for efficient test paper generating has been improved further. Experimental results show that the improved algorithm presented in this paper is efficient for the problem of genetic algorithm in premature and local optimization.