论文标题
产生合成人群
Generating Synthetic Population
论文作者
论文摘要
在本文中，我们提供了一种为印度等国家 /地区各个行政层面上产生综合人口的方法。该合成人群是使用机器学习和统计方法来调查数据（例如印度人口普查，IHDS-II，NSS-68回合，GPW等）创建的，合成人群定义了具有年龄，性别，身高，身高，体重，家庭和工作地点，家庭结构，家庭状况，社会经济状况，社会经济和雇用的人群中的人群中的个人。我们使用拟议的方法为印度各个地区生成合成人群。我们还使用各种指标将该合成人群与源数据进行了比较。实验结果表明，合成数据可以实际模拟印度各个地区的人口。
In this paper, we provide a method to generate synthetic population at various administrative levels for a country like India. This synthetic population is created using machine learning and statistical methods applied to survey data such as Census of India 2011, IHDS-II, NSS-68th round, GPW etc. The synthetic population defines individuals in the population with characteristics such as age, gender, height, weight, home and work location, household structure, preexisting health conditions, socio-economical status, and employment. We used the proposed method to generate the synthetic population for various districts of India. We also compare this synthetic population with source data using various metrics. The experiment results show that the synthetic data can realistically simulate the population for various districts of India.
