{"title":"人口预测的改进Leslie模型","authors":"Jinjing Ma, Yongkang Peng, Lianyu Wu","doi":"10.18282/l-e.v10i8.3060","DOIUrl":null,"url":null,"abstract":"Based on China’s population data from 1953 to 2020, the Leslie model combines the fertility rate of women of childbearing age by region and age, the sex ratio of the birth population, the mortality rate, the migration rate between urban and rural \nareas by age, the curve fitting migration function, and the application of ARIMA to predict mortality rates to construct a discrete \npopulation dynamics system in order to predict China’s future population development trajectory. The improved Leslie, Leslie, \nBP and Malthus models were compared in terms of error rates. The improved Leslie model was more stable than the rest of the \nmodels and had an average error rate of 0.09%, with good model generalization ability. The results show that the improved Leslie \nmodel predicts that the total population will slowly increase under the national regulation policy, and will reach a peak by around \n2045 and then decline.","PeriodicalId":199440,"journal":{"name":"Learning & Education","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Improved Leslie Model for population Forecasting\",\"authors\":\"Jinjing Ma, Yongkang Peng, Lianyu Wu\",\"doi\":\"10.18282/l-e.v10i8.3060\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on China’s population data from 1953 to 2020, the Leslie model combines the fertility rate of women of childbearing age by region and age, the sex ratio of the birth population, the mortality rate, the migration rate between urban and rural \\nareas by age, the curve fitting migration function, and the application of ARIMA to predict mortality rates to construct a discrete \\npopulation dynamics system in order to predict China’s future population development trajectory. The improved Leslie, Leslie, \\nBP and Malthus models were compared in terms of error rates. The improved Leslie model was more stable than the rest of the \\nmodels and had an average error rate of 0.09%, with good model generalization ability. The results show that the improved Leslie \\nmodel predicts that the total population will slowly increase under the national regulation policy, and will reach a peak by around \\n2045 and then decline.\",\"PeriodicalId\":199440,\"journal\":{\"name\":\"Learning & Education\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Learning & Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18282/l-e.v10i8.3060\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Learning & Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18282/l-e.v10i8.3060","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Improved Leslie Model for population Forecasting
Based on China’s population data from 1953 to 2020, the Leslie model combines the fertility rate of women of childbearing age by region and age, the sex ratio of the birth population, the mortality rate, the migration rate between urban and rural
areas by age, the curve fitting migration function, and the application of ARIMA to predict mortality rates to construct a discrete
population dynamics system in order to predict China’s future population development trajectory. The improved Leslie, Leslie,
BP and Malthus models were compared in terms of error rates. The improved Leslie model was more stable than the rest of the
models and had an average error rate of 0.09%, with good model generalization ability. The results show that the improved Leslie
model predicts that the total population will slowly increase under the national regulation policy, and will reach a peak by around
2045 and then decline.