【摘要】 利用RBF神经网络提出了一种基于脑信息特征的大学生心理问题判断模型.采用脑信息特征检测方法对180名临床诊断为有心理问题的大学生和300名心理正常的大学生进行了测试,并对测试的数据进行了脑信息特征提取.然后根据提取的脑信息特征及其他数据,利用RBF神经网络,建立了心理问题的判断模型和结合专家经验的两阶段判断方法.237名测试样本的实验结果表明正确率可达85.1%,因此该判断模型是可行的.更多还原

【Abstract】 This paper presented an estimation model on mental problems of undergraduates based on brain information features through RBFNN.180 subjects with mental problems and 300 subjects without mental problems were tested by brain information feature detection approach.And then,some features were extracted.Based on these features and other information,the estimation model was proposed.The experimental results from 237 samples show that the decision method is feasible,and the accuracy is 85.1%.更多还原