基于机器学习的各国可持续发展目标指标绩效比较分析

Anais do XVIII Encontro Nacional de Inteligência Artificial e Computacional (ENIAC 2021) Pub Date : 2021-11-29 DOI:10.5753/eniac.2021.18248

Guilherme Souza, J. Santos, Gabriel SantClair, Janaína Gomide, Luan Santos

{"title":"基于机器学习的各国可持续发展目标指标绩效比较分析","authors":"Guilherme Souza, J. Santos, Gabriel SantClair, Janaína Gomide, Luan Santos","doi":"10.5753/eniac.2021.18248","DOIUrl":null,"url":null,"abstract":"The Sustainable Development Goals (SDGs) are part of a global effort to reduce the impacts of climate change, promoting social justice and economic growth. The United Nations provides a database with hundreds of indicators to track the SDGs since 2016 for a total of 302 regions. This work aims to assess which countries are in a similar situation regarding sustainable development. Principal Component Analysis was used to reduce the dimension of the dataset and k-means algorithm was used to cluster countries according to their SDGs indicators. For the years of 2016, 2017 and 2018 were obtained 11, 13 and 11 groups, respectively. This paper also analyses clusters changes throughout the years.","PeriodicalId":318676,"journal":{"name":"Anais do XVIII Encontro Nacional de Inteligência Artificial e Computacional (ENIAC 2021)","volume":"117 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Comparative Analysis of Countries' Performance According to SDG Indicators based on Machine Learning\",\"authors\":\"Guilherme Souza, J. Santos, Gabriel SantClair, Janaína Gomide, Luan Santos\",\"doi\":\"10.5753/eniac.2021.18248\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Sustainable Development Goals (SDGs) are part of a global effort to reduce the impacts of climate change, promoting social justice and economic growth. The United Nations provides a database with hundreds of indicators to track the SDGs since 2016 for a total of 302 regions. This work aims to assess which countries are in a similar situation regarding sustainable development. Principal Component Analysis was used to reduce the dimension of the dataset and k-means algorithm was used to cluster countries according to their SDGs indicators. For the years of 2016, 2017 and 2018 were obtained 11, 13 and 11 groups, respectively. This paper also analyses clusters changes throughout the years.\",\"PeriodicalId\":318676,\"journal\":{\"name\":\"Anais do XVIII Encontro Nacional de Inteligência Artificial e Computacional (ENIAC 2021)\",\"volume\":\"117 4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Anais do XVIII Encontro Nacional de Inteligência Artificial e Computacional (ENIAC 2021)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5753/eniac.2021.18248\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Anais do XVIII Encontro Nacional de Inteligência Artificial e Computacional (ENIAC 2021)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5753/eniac.2021.18248","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

可持续发展目标(sdg)是减少气候变化影响、促进社会正义和经济增长的全球努力的一部分。自2016年以来，联合国提供了一个包含数百个指标的数据库，用于跟踪302个地区的可持续发展目标。这项工作的目的是评估哪些国家在可持续发展方面处于类似的情况。使用主成分分析对数据集进行降维，并使用k-means算法根据可持续发展目标指标对国家进行聚类。2016年、2017年和2018年分别获得11组、13组和11组。本文还分析了各年份的集群变化。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

A Comparative Analysis of Countries' Performance According to SDG Indicators based on Machine Learning

The Sustainable Development Goals (SDGs) are part of a global effort to reduce the impacts of climate change, promoting social justice and economic growth. The United Nations provides a database with hundreds of indicators to track the SDGs since 2016 for a total of 302 regions. This work aims to assess which countries are in a similar situation regarding sustainable development. Principal Component Analysis was used to reduce the dimension of the dataset and k-means algorithm was used to cluster countries according to their SDGs indicators. For the years of 2016, 2017 and 2018 were obtained 11, 13 and 11 groups, respectively. This paper also analyses clusters changes throughout the years.

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

Anais do XVIII Encontro Nacional de Inteligência Artificial e Computacional (ENIAC 2021)

自引率

0.00%

发文量