Preprocessing of samples in modeling of fetal macrosomia with counter propagation neural network

摘要：

In modeling of fetal macrosomia, some inconsistent data are mixed in samples. Because the procedure of childbearing has been finished, the sample data can not be validated by visiting previous pregnant woman. In order to eliminate the inaccurate samples, a counter propagation neural network is established. Some traditional methods are also used to verify the discarded samples. The new training set shows better classification than original data set.

关键词： fetal macrosomia preprocessing counter propagation artificial neural network(CPANN)

作者: Xu Zhipeng Shen Aifang

作者单位: School of Physics Science and InformationEngineering, Liaocheng UniversityLiaocheng, China Department of Gynaecology and Obstetrics Liaocheng Brain Hospital Liaocheng, China

会议类型: 国际会议

会议名称: 2011 IEEE 10th International Symposium on Distributed Computing and Applications to Business,Engineering(第十届电子商务、工程及科学领域的分布式计算和应用国际学术研讨会 DCABES 2011)

会议地点: 无锡

会议语种:英文

页码: 382-385

在线出版日期: 2011-10-14（万方平台首次上网日期，不代表论文的发表时间）