基于前馈神经网络的智慧城市空巢老人识别

Recognition of empty-nest elders in intelligent city based on feedforward neural network

随着社会老龄化进程的加快,空巢老人的数量呈上升趋势,老龄化成为一个不容忽视的社会问题.通过对空巢老人手机用户的识别的数据分析,提出识别信息完整的用户与信息缺失的用户的两个模型.基于正常的用户信息表,空巢老人及其子女的数量可以准确识别,当用户的信息不够充足时,采用前馈神经网络算法,结果显示其空巢老人的识别率可以达到73.3%.通过识别模型,及时更新空巢老人的数据,为统计局等政府部门提供了简单有效的数据分析,有助于建设智慧城市,促进社会和谐.

Aimed at the social problems associated with empty-nest elders, two recognition models of emptynest elders were presented based on the analysis of calling list and user information table. The empty-nest elders and their children’ number can be identified by recognition function based on the normal user information table. Meanwhile the recognition accuracy rate can reach 73.3% using feedforward neural network algorithm when the information of a user is not sufficient. Moreover the database empty-nest elders can be timely updated by the recognition models, which can provide effective data for statistics bureau and other government departments. It is beneficial to the development of intelligent city and harmonious society.