The quality of the airwe breathe during the courses of our daily lives has a significant impact on our health and well-being as individuals.Unfortunately,personal air quality measurement remains challenging.In this st...The quality of the airwe breathe during the courses of our daily lives has a significant impact on our health and well-being as individuals.Unfortunately,personal air quality measurement remains challenging.In this study,we investigate the use of first-person photos for the prediction of air quality.The main idea is to harness the power of a generalized stacking approach and the importance of haze features extracted from first-person images to create an efficient new stacking model called AirStackNet for air pollution prediction.AirStackNet consists of two layers and four regression models,where the first layer generates meta-data fromLight Gradient Boosting Machine(Light-GBM),Extreme Gradient Boosting Regression(XGBoost)and CatBoost Regression(CatBoost),whereas the second layer computes the final prediction from the meta-data of the first layer using Extra Tree Regression(ET).The performance of the proposed AirStackNet model is validated using public Personal Air Quality Dataset(PAQD).Our experiments are evaluated using Mean Absolute Error(MAE),Root Mean Square Error(RMSE),Coefficient of Determination(R2),Mean Squared Error(MSE),Root Mean Squared Logarithmic Error(RMSLE),and Mean Absolute Percentage Error(MAPE).Experimental Results indicate that the proposed AirStackNet model not only can effectively improve air pollution prediction performance by overcoming the Bias-Variance tradeoff,but also outperforms baseline and state of the art models.展开更多
本文利用中尺度非静力WRF(Weather Research Forecast,Version 3.4)模式,针对1013号"鲇鱼"台风个例,通过对红外高光谱AIRS(Atmospheric Infrared Sounder)资料经过基于空间梯度信息的质量控制之后同化进入模式,来评估新的质...本文利用中尺度非静力WRF(Weather Research Forecast,Version 3.4)模式,针对1013号"鲇鱼"台风个例,通过对红外高光谱AIRS(Atmospheric Infrared Sounder)资料经过基于空间梯度信息的质量控制之后同化进入模式,来评估新的质量控制方法对同化效果的影响以及对台风数值模拟的改善情况。研究结果发现,如果仅仅基于WRFDA(WRF Data Assimilation system,Version 3.4)模式自带的质量控制系统,将会有部分梯度距平值明显较大超过阈值的资料被同化进入模式,而这些可能受到"污染"且误差较大的资料同化进入模式必将会导致同化结果有较大误差,影响分析结果的质量。而对AIRS资料经过基于空间梯度信息质量控制之后再同化进入模式,确实可将梯度距平值大于阈值的"坏点"剔除掉,从而使初始场的描述更加准确,台风路径的模拟精度在一定程度上得到提高。综上可知,基于空间梯度信息的质量控制方法整体上对改善同化效果有较好的正效应,对台风的数值模拟也起到一定的促进作用。展开更多
利用高精度和稳定的AIRS/Aqua(Atmospheric InfraRed Sounder on board Aqua)数据对SVISSR/FY-2C(Stretched Visible and Infrared SpinScan Radiometer on board Feng Yun 2C)的两个分裂窗通道IR1(Infra Red 1,10.9μm)和IR2(InfraRed ...利用高精度和稳定的AIRS/Aqua(Atmospheric InfraRed Sounder on board Aqua)数据对SVISSR/FY-2C(Stretched Visible and Infrared SpinScan Radiometer on board Feng Yun 2C)的两个分裂窗通道IR1(Infra Red 1,10.9μm)和IR2(InfraRed 2,11.9μm)进行交叉辐射定标的方法,并利用赤道附近2006年12月和2007年12月的AIRS和SVISSR数据完成了交叉辐射定标,结果表明,SVISSR数据与卷积得到的AIRS数据高度线性相关,SVISSR/FY-2C传感器的两个分裂窗通道不仅存在定标误差,而且定标误差随时间的变化呈现增大的趋势。相对于AIRS/Aqua测量值,当SVISSR的通道亮温从220K变化到340K时,2006年12月IR1通道的温度调整量从5.8K变化到-4.4K,而2007年12月IR1通道的温度调整量从6.9K变化到-5.1K;2006年12月IR2通道的温度调整量从2.2K变化到-1.5K,而2007年12月IR2通道的温度调整量从6.3K变化到-6.1K。展开更多
基金the Deputyship for Research and Innovation,Ministry of Education in Saudi Arabia for funding this research through project number PNU-DRI-RI-20-033.
文摘The quality of the airwe breathe during the courses of our daily lives has a significant impact on our health and well-being as individuals.Unfortunately,personal air quality measurement remains challenging.In this study,we investigate the use of first-person photos for the prediction of air quality.The main idea is to harness the power of a generalized stacking approach and the importance of haze features extracted from first-person images to create an efficient new stacking model called AirStackNet for air pollution prediction.AirStackNet consists of two layers and four regression models,where the first layer generates meta-data fromLight Gradient Boosting Machine(Light-GBM),Extreme Gradient Boosting Regression(XGBoost)and CatBoost Regression(CatBoost),whereas the second layer computes the final prediction from the meta-data of the first layer using Extra Tree Regression(ET).The performance of the proposed AirStackNet model is validated using public Personal Air Quality Dataset(PAQD).Our experiments are evaluated using Mean Absolute Error(MAE),Root Mean Square Error(RMSE),Coefficient of Determination(R2),Mean Squared Error(MSE),Root Mean Squared Logarithmic Error(RMSLE),and Mean Absolute Percentage Error(MAPE).Experimental Results indicate that the proposed AirStackNet model not only can effectively improve air pollution prediction performance by overcoming the Bias-Variance tradeoff,but also outperforms baseline and state of the art models.
文摘本文利用中尺度非静力WRF(Weather Research Forecast,Version 3.4)模式,针对1013号"鲇鱼"台风个例,通过对红外高光谱AIRS(Atmospheric Infrared Sounder)资料经过基于空间梯度信息的质量控制之后同化进入模式,来评估新的质量控制方法对同化效果的影响以及对台风数值模拟的改善情况。研究结果发现,如果仅仅基于WRFDA(WRF Data Assimilation system,Version 3.4)模式自带的质量控制系统,将会有部分梯度距平值明显较大超过阈值的资料被同化进入模式,而这些可能受到"污染"且误差较大的资料同化进入模式必将会导致同化结果有较大误差,影响分析结果的质量。而对AIRS资料经过基于空间梯度信息质量控制之后再同化进入模式,确实可将梯度距平值大于阈值的"坏点"剔除掉,从而使初始场的描述更加准确,台风路径的模拟精度在一定程度上得到提高。综上可知,基于空间梯度信息的质量控制方法整体上对改善同化效果有较好的正效应,对台风的数值模拟也起到一定的促进作用。
文摘利用高精度和稳定的AIRS/Aqua(Atmospheric InfraRed Sounder on board Aqua)数据对SVISSR/FY-2C(Stretched Visible and Infrared SpinScan Radiometer on board Feng Yun 2C)的两个分裂窗通道IR1(Infra Red 1,10.9μm)和IR2(InfraRed 2,11.9μm)进行交叉辐射定标的方法,并利用赤道附近2006年12月和2007年12月的AIRS和SVISSR数据完成了交叉辐射定标,结果表明,SVISSR数据与卷积得到的AIRS数据高度线性相关,SVISSR/FY-2C传感器的两个分裂窗通道不仅存在定标误差,而且定标误差随时间的变化呈现增大的趋势。相对于AIRS/Aqua测量值,当SVISSR的通道亮温从220K变化到340K时,2006年12月IR1通道的温度调整量从5.8K变化到-4.4K,而2007年12月IR1通道的温度调整量从6.9K变化到-5.1K;2006年12月IR2通道的温度调整量从2.2K变化到-1.5K,而2007年12月IR2通道的温度调整量从6.3K变化到-6.1K。
