Application of BP Neural Network Based on Genetic Algorithms Optimization in Prediction of Postgraduate Entrance Examination

被引:9
作者
Chi, Li [1 ]
Lin, Li [1 ]
机构
[1] Sichuan Univ, Jincheng Coll, Dept Comp Sci & Software Engn, Chengdu, Peoples R China
来源
2016 3RD INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CONTROL ENGINEERING (ICISCE) | 2016年
关键词
postgraduate entrance examination; prediction; BP neural network; genetic algorithms;
D O I
10.1109/ICISCE.2016.57
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The initial weights and thresholds of BP neural network are optimized by genetic algorithm in advance, and then the BP neural network is used in the prediction model of the postgraduate entrance examination results. Experimental results show that the optimized prediction model due to overcome the slow convergence speed and the defects of easy to produce local minimum has better accuracy than prediction model established by BP neural network alone, and is better than the traditional K-Nearest Neighbor and Naive Bayes classification results. The prediction model will be provided to the students before registration for postgraduate entrance examination, which is convenient for students to make reasonable decision, which has certain practical significance.
引用
收藏
页码:226 / 229
页数:4
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