(AE 2010) An enhanced PM2.5 air quality forecast model based on nonlinear regression and back-trajec

可参考的表达方式:

The enhanced PM2.5 model was compared with three alternative models, including the basic NLR model, the basic NLR model with a persistence parameter added, and the NLR model with persistence and PM24.

本文作者在表达增强PM2.5模型与其他三种模型对比时,其他三种模型表述为 three alternative models(三种替代模型),而且,在表述每种模型时,均使用了特指 the,在模型介绍较长时采用逗号分隔。

(AE 2010) An enhanced PM2.5 air quality forecast model based on nonlinear regression and back-trajec

 在图2的介绍中,用于展示气温、风速和PM2.5浓度三者之间关系的多层散点图被表述为 Data exploratory analysis,另外,在告知数据来源之前,作者用一句话表达出该图的核心要点。

(AE 2010) An enhanced PM2.5 air quality forecast model based on nonlinear regression and back-trajec

 由于图6是将PM2.5、O3和温度的时间序列堆叠在一起进行展示,作者将其表述为 Stacked time series plots,同样,作者用一句话表达出该图的核心要点。

(AE 2010) An enhanced PM2.5 air quality forecast model based on nonlinear regression and back-trajec

 可参考表2的描述方式,性能指标(Forecast Accuracy and critical forecast performance)for 模型 during 时间段

 

主要结论:

1. PM24(additional parameter based on upwind PM2.5 concentration)作为模型输入可以明显提升PM2.5的预测准确度

2. 加入固定(persistence)参数的效果会比单纯使用气象数据预测要好,但是不及加入PM24的效果

 

上一篇:单利模式-恶汉式


下一篇:2.单例模式