《计算机应用研究》|Application Research of Computers

一种考虑风力作用的KNN城市AQI预测算法

K-nearest neighbor urban forecasting algorithm considering wind factors

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作者 杨丰玉,王宝英,陈英,冯涛,陈涛苹
机构 南昌航空大学 软件学院,南昌 330063
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文章编号 1001-3695(2019)06-017-1679-04
DOI 10.19734/j.issn.1001-3695.2017.12.0797
摘要 考虑风力对城市空气质量指数(AQI)的重要影响,基于KNN算法提出一种新的模型对城市AQI进行预测。该模型主要依赖于数据间的局部相似性和依赖性,再将风力因素对城市AQI的影响进行量化并加入到KNN预测结果中,得到最终预测结果。实验对九个重点城市进行AQI预测,结果表明,该模型相较传统KNN方法预测得到的AQI值准确率大幅度提升,对城市AQI的预测具有指导意义。
关键词 空气质量指数; K近邻; 风力因素; 预测
基金项目 江西省自然科学基金资助项目(20161BAB212034)
本文URL http://www.arocmag.com/article/01-2019-06-017.html
英文标题 K-nearest neighbor urban forecasting algorithm considering wind factors
作者英文名 Yang Fengyu, Wang Baoying, Chen Ying, Feng Tao, Chen Taoping
机构英文名 School of Software,Nanchang Hangkong University,Nanchang 330063,China
英文摘要 Considering the important influence of wind on air quality index(AQI), this paper proposed a new model, which based on KNN algorithm to predict the urban AQI. The model mainly relied on the local similarity and dependence between data, and quantified the impact of wind factors on urban AQI and added it to the KNN forecast results to get the final forecast results. The experimental results of AQI in nine major cities show that the proposed model significantly improves the accuracy of AQI compared with the traditional KNN method. The model has guiding significance for the prediction of urban AQI.
英文关键词 air quality index(AQI); K-nearest neighbor(KNN); wind factors; forecast
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收稿日期 2017/12/7
修回日期 2018/1/25
页码 1679-1682,1722
中图分类号 TP301.6
文献标志码 A