The Multivariate Gray Model approach to Predict the Concentration of Atmospheric Fine PM2.5

机译：多变量灰色模型方法预测大气浓度PM2.5的浓度

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摘要

The problem of atmospheric pollution has become the primary issue all over the world. The atmospheric pollution of the subtle particles PM2.5 has already cause a serious threat to people's health. This passage is on the side of the causes and the characteristics of this problem. Structurina multivariate grey to prove that the model is accurately through the experiment with great applied on the part of atmospheric pollution.

机译：大气污染问题已成为世界各地的主要问题。微妙粒子PM2.5的大气污染已经对人们的健康造成严重威胁。这段经文是在原因的一侧和这个问题的特征。 STRUCTURINA多变灰度证明该模型通过实验准确地应用于大气污染的部分。

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《International Conference on Energy and Environmental Protection》|2014年||共4页
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Jiayang Li; Zhao yang; Shenkai Shi;
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中图分类 TB3-532;
关键词
gray model; PM2.5; multivariate gray model; atmospheric fine;

机译：灰色模型;PM2.5;多变量灰色模型;大气精细;

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1. A system based approach to develop hybrid model predicting extreme urban NOx and PM2.5 concentrations [J] . Gulia Sunil, Nagendra S. M. Shiva, Khare Mukesh Transportation Research . 2017,第octa期

机译：一种基于系统的方法来开发混合模型，预测极端的城市NOx和PM2.5浓度
2. Concentrations of Ni and V, other heavy metals, arsenic, elemental and organic carbon in atmospheric fine particles (PM2.5) from Puerto Rico. [J] . Figueroa DA, Rodriguez Sierra CJ, Jimenez Velez BD Toxicology and Industrial Health . 2006,第2期

机译：波多黎各的大气微粒（PM2.5）中的镍和钒，其他重金属，砷，元素和有机碳的浓度。
3. A semi-empirical model for predicting hourly ground-level fine particulate matter (PM2.5) concentration in southern Ontario from satellite remote sensing and ground-based meteorological measurements [J] . Tian J, Chen DM Remote Sensing of Environment: An Interdisciplinary Journal . 2010,第2期

机译：通过卫星遥感和地面气象测量来预测安大略省南部每小时细小颗粒物（PM2.5）浓度的半经验模型
4. The Multivariate Gray Model approach to Predict the Concentration of Atmospheric Fine PM2.5 [C] . Jiayang Li, Zhao yang, Shenkai Shi International Conference on Energy and Environmental Protection . 2014

机译：多变量灰色模型方法预测大气浓度PM2.5的浓度
5. Comparison of Models for Predicting PM2.5 Concentration in Wuhan, China [D] . Chen, Xiaohe. 2018

机译：武汉预测PM2.5集中模型的比较
6. Concentrations of Ni and V other heavy metals arsenic elemental and organic carbon in atmospheric fine particles (PM2.5) from Puerto Rico [O] . David Acevedo Figueroa, Carlos J Rodríguez-Sierra, Braulio D Jiménez-Velez -1

机译：波多黎各的大气微粒（PM2.5）中的镍和钒其他重金属砷元素和有机碳的浓度
7. Comparative Performance of Different Statistical Models for Predicting Ground-Level Ozone (O3) and Fine Particulate Matter (PM2.5) Concentrations in Montréal, Canada [O] . Martin Edouard Philippe 2011

机译：预测加拿大蒙特利尔的地面臭氧（O3）和细颗粒物（PM2.5）浓度的不同统计模型的比较性能
8. Predictive Approach on the Detection of Additional Information in a Multivariate Linear Model [R] . Dewaal, D. J., Nel, D. G. 1981

机译：多元线性模型中附加信息检测的预测方法

The Multivariate Gray Model approach to Predict the Concentration of Atmospheric Fine PM2.5

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