文章采用贝叶斯网络来学习和构造流动妇女收入影响因素系统,通过比较不同算法下贝叶斯网络结构的差异,说明江苏流动妇女收入影响因素之间的关系,为研究复杂社会问题提供一种简便、有效的方法。研究发现,城市是影响流动妇女职业和收入的关键变量,受教育程度和培训并不直接影响流动妇女的职业和收入。
Due to the uncertainty of the factors that influence the income and other characters of floating women in Jiangsu province,Bayesian Network is used to model this kind of system.Different algorithms are used for learning Bayesian Networks in order to compare several models.It is suggested that researchers can use Bayesian Networks to explore the potential relationship between variables of complex social problems.The result indicates that city is the key variable which influenced floating wom-an’s job and income.Education and training experience didn’t influenced floating woman’s job and income directly.