基于树系集合模型的空气污染心肺死亡率预测

IF 0.7 Q3 COMPUTER SCIENCE, THEORY & METHODS
Akibu Mahmoud Abdullahi
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引用次数: 0

摘要

空气污染对人类福祉和健康产生重大负面影响。心肺死亡是空气污染的主要影响之一。在本研究中,我们分析了空气污染与心肺死亡率的关系,并利用基于树的集合模型预测了基于空气污染的心肺死亡率。本研究中使用的基于树的集成模型是投票回归(VR)、随机森林(RF)、梯度树增强(GB)和极端梯度增强(XGBoost)。使用的数据集包含五个研究地点的数据:沙阿南(SA),巴生(KLN),布城(PUJ),谢拉斯,吉隆坡(CKL)和八打灵查亚(PJ),从2006年1月到2016年12月。结果表明,在巴生研究区域,XGBoost和VR模型优于其他评价指标得分最高的模型,XGBoost(MAE:0.005, RMSE:0.010, MAPE:0.70%)和VR (MAE:0.005, RMSE:0.011, MAPE:0.70%)。结果表明,所建立的模型能较好地预测基于空气污染的心肺疾病死亡率,并能较好地反映心肺疾病死亡率的变化趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cardiorespiratory Mortality Prediction Based on Air Pollution Using Tree-Based Ensemble Models
Air pollution has a substantial negative impact on human wellbeing and health. Cardiorespiratory mortality is one of the primary effects of air pollution. In this study, we provide analysis of air pollution, cardiorespiratory mortality and the cardiorespiratory mortality is predicted based on air pollution using tree-based ensemble models. The tree-based ensemble models utilized in this study are Voting Regressor (VR), Random Forest (RF), Gradient Tree Boosting (GB), and Extreme Gradient Boosting (XGBoost). The used dataset contains data for five research locations: Shah Alam (SA), Klang (KLN), Putrajaya (PUJ), Cheras, Kuala Lumpur (CKL), and Petaling Jaya (PJ) from January 2006 to December 2016. The results show that XGBoost and VR models outperformed the rest of the models with the best evaluation metric scores in the Klang study area, XGBoost(MAE:0.005, RMSE:0.010, MAPE:0.70%) and VR (MAE:0.005, RMSE:0.011, MAPE:0.70%). The results reveal that the utilized models provided an excellent and accurate prediction of cardiorespiratory mortality based on air pollution and can follow the trend of cardiorespiratory mortality.
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来源期刊
CiteScore
2.30
自引率
22.20%
发文量
519
期刊介绍: IJACSA is a scholarly computer science journal representing the best in research. Its mission is to provide an outlet for quality research to be publicised and published to a global audience. The journal aims to publish papers selected through rigorous double-blind peer review to ensure originality, timeliness, relevance, and readability. In sync with the Journal''s vision "to be a respected publication that publishes peer reviewed research articles, as well as review and survey papers contributed by International community of Authors", we have drawn reviewers and editors from Institutions and Universities across the globe. A double blind peer review process is conducted to ensure that we retain high standards. At IJACSA, we stand strong because we know that global challenges make way for new innovations, new ways and new talent. International Journal of Advanced Computer Science and Applications publishes carefully refereed research, review and survey papers which offer a significant contribution to the computer science literature, and which are of interest to a wide audience. Coverage extends to all main-stream branches of computer science and related applications
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