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Evaluation of Artificial Neural Networks for Fine Particulate Pollution (PM10 and PM2.5) Forecasting

机译：细颗粒污染人工神经网络评价（PM10和PM2.5）预测

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Ian G. McKendry;
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年度 2002
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1. Discovering relationships and forecasting PM10 and PM2.5 concentrations in Bogotá, Colombia, using Artificial Neural Networks, Principal Component Analysis, and k-means clustering [J] . Fabiana Franceschi, Martha Cobo, Manuel Figueredo Atmospheric Pollution Research . 2018,第5期

机译：使用人工神经网络，主成分分析和K-means聚类，在哥伦比亚的PM10和PM10和PM2.5浓度中发现关系和预测。
2. Artificial neural networks forecasting of PM2.5 pollution using air mass trajectory based geographic model and wavelet transformation [J] . Feng Xiao, Li Qi, Zhu Yajie, Atmospheric environment . 2015,第apra期

机译：基于空气质量轨迹的地理模型和小波变换的人工神经网络预测PM2.5污染
3. Universal system for forecasting changes in PM10 and PM2.5 particulate matter air pollution concentration [J] . Lasiewicz Marek, Bogusz Malgorzata, Kosla Magdalena International Journal of Environment and Pollution . 2015,第1a4期

机译：预测PM10和PM2.5颗粒物质空气污染浓度的普遍系统
4. Evaluating Particulate Matter (PM2.5 and PM10) Impact on Human Health in Oman Based on a Hybrid Artificial Neural Network and Mathematical Models [C] . Nebras Alattar, Jabar Yousif International Conference on Control, Artificial Intelligence, Robotics Optimization . 2019

机译：基于混合人工神经网络和数学模型的颗粒物（PM2.5和PM10）对阿曼人体健康的影响评估
5. Near-roadway Air Pollution: Evaluation of Fine Particulate Matter (PM2.5) and Ultrafine Particulate Matter (PM0.1) in Interior Alaska [D] . Kadir, Abdul. 2019

机译：近巷道空气污染：在内部阿拉斯加内部的细颗粒物（PM2.5）和超细颗粒物（PM0.1）的评价
6. Temporal and Spatial Simulation of Atmospheric Pollutant PM2.5 Changes and Risk Assessment of Population Exposure to Pollution Using Optimization Algorithms of the Back Propagation-Artificial Neural Network Model and GIS [O] . Ping Zhang, Bo Hong, Liang He, 2015

机译：反向传播-人工神经网络模型和GIS优化算法对大气污染物PM2.5变化的时空模拟和人口污染风险评估
7. The evaluation on artificial neural networks (ANN) and multiple linear regressions (MLR) models over particulate matter (PM10) variability during haze and non-haze episodes: A decade case study [O] . Ku Mohd Kalkausar Ku Yusof, Azman Azid, Muhamad Shirwan Abdullah Sani, 2019

机译：在雾度和非雾度集中的颗粒物质（PM10）变异性上的人工神经网络（ANN）和多元线性回归（MLR）模型的评价：十年的案例研究

Evaluation of Artificial Neural Networks for Fine Particulate Pollution (PM10 and PM2.5) Forecasting

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