Universal system for forecasting changes in PM 10 and PM 2.5 particulate matter air pollution concentration
Universal system for forecasting changes in PM 10 and PM 2.5 particulate matter air pollution concentration
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DOI：
10.1504/ijep.2014.067692
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发表时间：
2014
影响因子：
0.7
通讯作者：
Marek Lasiewicz;Małgorzata Bogusz;M. Kośla
中科院分区：
文献类型：
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作者：
Marek Lasiewicz;Małgorzata Bogusz;M. Kośla
我们提出了一个系统，用于预测PM 10和PM 2.5颗粒物空气污染浓度的变化。该系统的基础上，从华沙（波兰）的环境保护省（区域）监察局的自动测量站的immissations数据和气象参数的数值预报从数学和计算建模，华沙大学跨学科中心。该计划的概念是基于人工神经网络以及支持向量机在回归模式下工作的各种模型。该方法使用小波分解和盲源分离更好，更准确的预测。这一通用系统提供了一个工具，用于对PM 10和PM 2.5的每日最高水平进行预警，并致力于地方当局评估环境恢复计划的生态效率。
We present a system for forecasting the changes in PM 10 and PM 2.5 particulate matter air pollution concentration . The system is based on immissions data from automatic measurement stations of the Voivodship (Regional) Inspectorate for Environmental Protection in Warsaw (Poland) and a numerical forecast of meteorological parameters from the Interdisciplinary Centre for Mathematical and Computational Modelling, Warsaw University. The concept of the program is based on various models based on artificial neural networks as well as a support vector machine working in regression mode. The approach uses wavelet decomposition and Blind Source Separation for better, more accurate forecasting. This universal system provides a tool for early warning of exceedance of daily maximum levels of PM 10 and PM 2.5 and is dedicated to local authorities to evaluate the ecological efficiency of environmental recovery programs.