{"title":"基于系统动力学模型的中国铜需求预测:2016-2030年","authors":"Jianbo Yang, Xin Li, Qunyi Liu","doi":"10.20944/PREPRINTS201703.0231.V1","DOIUrl":null,"url":null,"abstract":"This paper assumes that China's economy will be developing high, medium and low scenarios, and forecasts economic and social indicators such as total GDP, population and per capita GDP in China from 2016 to 2030. Then, predicted the demand of copper resources in China from 2016 to 2030 by the combination of system dynamics model, ARIMA model prediction and inverted U-type empirical model. The results show that: China's copper demand growth slowed down significantly from 2016-2030. From 2025-2030, China's copper resource demand is stable, into the platform of demand growth. 2030 years later, China's copper resource dem and will enter a slow decline.","PeriodicalId":17101,"journal":{"name":"Journal of Residuals Science & Technology","volume":"8 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2017-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"China's Copper Demand Forecasting Based on System Dynamics Model: 2016-2030\",\"authors\":\"Jianbo Yang, Xin Li, Qunyi Liu\",\"doi\":\"10.20944/PREPRINTS201703.0231.V1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper assumes that China's economy will be developing high, medium and low scenarios, and forecasts economic and social indicators such as total GDP, population and per capita GDP in China from 2016 to 2030. Then, predicted the demand of copper resources in China from 2016 to 2030 by the combination of system dynamics model, ARIMA model prediction and inverted U-type empirical model. The results show that: China's copper demand growth slowed down significantly from 2016-2030. From 2025-2030, China's copper resource demand is stable, into the platform of demand growth. 2030 years later, China's copper resource dem and will enter a slow decline.\",\"PeriodicalId\":17101,\"journal\":{\"name\":\"Journal of Residuals Science & Technology\",\"volume\":\"8 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Residuals Science & Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.20944/PREPRINTS201703.0231.V1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Residuals Science & Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20944/PREPRINTS201703.0231.V1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
China's Copper Demand Forecasting Based on System Dynamics Model: 2016-2030
This paper assumes that China's economy will be developing high, medium and low scenarios, and forecasts economic and social indicators such as total GDP, population and per capita GDP in China from 2016 to 2030. Then, predicted the demand of copper resources in China from 2016 to 2030 by the combination of system dynamics model, ARIMA model prediction and inverted U-type empirical model. The results show that: China's copper demand growth slowed down significantly from 2016-2030. From 2025-2030, China's copper resource demand is stable, into the platform of demand growth. 2030 years later, China's copper resource dem and will enter a slow decline.
期刊介绍:
The international Journal of Residuals Science & Technology (JRST) is a blind-refereed quarterly devoted to conscientious analysis and commentary regarding significant environmental sciences-oriented research and technical management of residuals in the environment. The journal provides a forum for scientific investigations addressing contamination within environmental media of air, water, soil, and biota and also offers studies exploring source, fate, transport, and ecological effects of environmental contamination.