基于爱荷华算子的安徽省居民消费水平组合预测研究

Zihan Li
{"title":"基于爱荷华算子的安徽省居民消费水平组合预测研究","authors":"Zihan Li","doi":"10.9734/ajpas/2023/v25i1540","DOIUrl":null,"url":null,"abstract":"Aims: In order to study the future trend of Anhui residents’ consumption level and predict the consumption level of Anhui residents in the next three years (2022-2024), this paper constructs a combination prediction model based on the induced ordered weighted averaging (IOWA) operator.
 Study Design: This paper selects the national resident consumption level in Anhui province from 2000 to 2021, which covers a period of 21 years. Based on the data, an IOWA operator combination prediction model is constructed using a multiple regression model, ARIMA (2,2,0) model, and machine learning decision tree model. This is a qualitative analytical study which set the sum of squared errors as dependent variables and error value of different single item prediction method as independent variables.
 Place and Duration of Study: This paper selects the national resident consumption level in Anhui Province from 2000 to 2021.
 Methodology: This paper constructs a combination prediction model based on the IOWA operator based on the multiple regression model, ARIMA (2,2,0) model, and machine learning decision tree model. The combination prediction method that minimizes the sum of squared errors is used to predict the consumption level of Anhui residents in the next three years (2022-2024), and the effectiveness of the IOWA operator-based combination prediction model is evaluated.
 Results: This study finds that the prediction accuracy of the IOWA operator-based combination prediction model is generally greater than that of individual prediction models, and the sum of squared errors is generally significantly lower than that of individual prediction models.
 Conclusion: The prediction results show that the consumption level of Anhui residents in the next three years will not fluctuate greatly, but will have a trend of slight increase. The results of this study can be helpful for the government to improve the consumption level of residents in Anhui Province.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Study on the Combination Prediction of Anhui Residents’ Consumption Level Based on the IOWA Operator\",\"authors\":\"Zihan Li\",\"doi\":\"10.9734/ajpas/2023/v25i1540\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aims: In order to study the future trend of Anhui residents’ consumption level and predict the consumption level of Anhui residents in the next three years (2022-2024), this paper constructs a combination prediction model based on the induced ordered weighted averaging (IOWA) operator.
 Study Design: This paper selects the national resident consumption level in Anhui province from 2000 to 2021, which covers a period of 21 years. Based on the data, an IOWA operator combination prediction model is constructed using a multiple regression model, ARIMA (2,2,0) model, and machine learning decision tree model. This is a qualitative analytical study which set the sum of squared errors as dependent variables and error value of different single item prediction method as independent variables.
 Place and Duration of Study: This paper selects the national resident consumption level in Anhui Province from 2000 to 2021.
 Methodology: This paper constructs a combination prediction model based on the IOWA operator based on the multiple regression model, ARIMA (2,2,0) model, and machine learning decision tree model. The combination prediction method that minimizes the sum of squared errors is used to predict the consumption level of Anhui residents in the next three years (2022-2024), and the effectiveness of the IOWA operator-based combination prediction model is evaluated.
 Results: This study finds that the prediction accuracy of the IOWA operator-based combination prediction model is generally greater than that of individual prediction models, and the sum of squared errors is generally significantly lower than that of individual prediction models.
 Conclusion: The prediction results show that the consumption level of Anhui residents in the next three years will not fluctuate greatly, but will have a trend of slight increase. The results of this study can be helpful for the government to improve the consumption level of residents in Anhui Province.\",\"PeriodicalId\":8532,\"journal\":{\"name\":\"Asian Journal of Probability and Statistics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Asian Journal of Probability and Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.9734/ajpas/2023/v25i1540\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asian Journal of Probability and Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.9734/ajpas/2023/v25i1540","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

目的:为研究安徽省居民消费水平未来趋势,预测未来3年(2022-2024年)安徽省居民消费水平,构建了基于诱导有序加权平均(IOWA)算子的组合预测模型。研究设计:本文选取安徽省2000 - 2021年的全国居民消费水平,时间跨度为21年。在此基础上,利用多元回归模型、ARIMA(2,2,0)模型和机器学习决策树模型构建了IOWA算子组合预测模型。本研究是以误差平方和为因变量,以不同单项预测方法的误差值为自变量的定性分析研究。 研究地点和时间:本文选取安徽省2000 - 2021年全国居民消费水平。 方法:在多元回归模型、ARIMA(2,2,0)模型和机器学习决策树模型的基础上,构建了基于IOWA算子的组合预测模型。采用误差平方和最小的组合预测方法对未来3年(2022-2024年)安徽居民消费水平进行预测,并对基于IOWA算子的组合预测模型的有效性进行评价。 结果:本研究发现,基于IOWA算子的组合预测模型的预测精度普遍大于单个预测模型,误差平方和普遍显著低于单个预测模型。 结论:预测结果表明,未来3年安徽居民消费水平不会有较大波动,有小幅上升的趋势。研究结果可为安徽省政府提高居民消费水平提供参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study on the Combination Prediction of Anhui Residents’ Consumption Level Based on the IOWA Operator
Aims: In order to study the future trend of Anhui residents’ consumption level and predict the consumption level of Anhui residents in the next three years (2022-2024), this paper constructs a combination prediction model based on the induced ordered weighted averaging (IOWA) operator. Study Design: This paper selects the national resident consumption level in Anhui province from 2000 to 2021, which covers a period of 21 years. Based on the data, an IOWA operator combination prediction model is constructed using a multiple regression model, ARIMA (2,2,0) model, and machine learning decision tree model. This is a qualitative analytical study which set the sum of squared errors as dependent variables and error value of different single item prediction method as independent variables. Place and Duration of Study: This paper selects the national resident consumption level in Anhui Province from 2000 to 2021. Methodology: This paper constructs a combination prediction model based on the IOWA operator based on the multiple regression model, ARIMA (2,2,0) model, and machine learning decision tree model. The combination prediction method that minimizes the sum of squared errors is used to predict the consumption level of Anhui residents in the next three years (2022-2024), and the effectiveness of the IOWA operator-based combination prediction model is evaluated. Results: This study finds that the prediction accuracy of the IOWA operator-based combination prediction model is generally greater than that of individual prediction models, and the sum of squared errors is generally significantly lower than that of individual prediction models. Conclusion: The prediction results show that the consumption level of Anhui residents in the next three years will not fluctuate greatly, but will have a trend of slight increase. The results of this study can be helpful for the government to improve the consumption level of residents in Anhui Province.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信