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.

关键词： genetic algorithm BP neural network intelligent test paper generation

作者: Chao Liu Yan Hu

作者单位: College of Computer Science and Technology,Wuhan University of Technology,Wuhan,China

会议类型: 国际会议

会议名称: 2017年第2届联合国际信息技术、机械与电子工程国际会议(JIMEC2017)

会议地点: 重庆

会议语种:英文

页码: 157-160

在线出版日期: 2017-10-04（万方平台首次上网日期，不代表论文的发表时间）