摘要
针对当前对大学生人力资本与就业满意度问题,提出运用遗传算法优化的BP神经网络模型研究的方法。首先建立了大学生人力资本和就业满意度的指标体系;然后,使用递阶遗传算法优化BP神经网络;再使用优化后的模型对真实数据进行了训练及测试,并与传统BP模型测试结果进行了对比;优化后的效果较为明显。最后通过关联分析,得出各人力资本指标变动对就业指标影响的图表。
Considering the prevalent issue of the graduate human capital and the satisfactory for the employ- ment, a method using BP neural network model optimized by hierarchical genetic algorithm is proposed to study the relationship of this two. An index system of these two is constructed at the first place, then the BP neural network model optimized by genetic algorithm is constructed; subsequently, the optimized model is training under the real data and a comparison is made by the conventional model; the model achieves a relative remarkable re- sult; finally, a graph for the influence of satisfactory index generated by the changing of the human capital comes out after the correlation analysis.
出处
《科技创业月刊》
2013年第7期67-70,共4页
Journal of Entrepreneurship in Science & Technology
关键词
人力资本
就业
BP神经网络
递阶遗传算法
优化
human capital
employment
BP neural network
hierarchical genetic algorithm
optimization
