NEURAL NETWORK PREDICTION MODELS AS A TOOL FOR AIR QUALITY MANAGEMENT IN CITIES

被引：0

作者：

Skrzypski, Jerzy ^{[1
]}

Jach-Szakiel, Emilia ^{[1
]}

机构：

[1] Tech Univ Lodz, Fac Proc & Environm Engn, PL-90924 Lodz, Poland

来源：

ENVIRONMENT PROTECTION ENGINEERING | 2008年 / 34卷 / 04期

关键词：

D O I：

暂无

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

The aim of the study was to examine the possibilities of developing a prognostic methods for the air quality management in cities. The study was focused on the development of the neural network models for predicting the classes of air quality in terms of the daily dust PM(10) concentration. The air quality class was predicted for the following day based on average and maximal daily concentrations. The MLP and RBF models were tested and the results obtained proved to be satisfactory. In the optimal models, false prognoses (in testing series) constituted only 1.9% in the case of predicting average daily concentration and 7.4% in the case of predicting maximum daily concentration. A small prediction error confirmed that neural network models can be an effective tool for the air quality management in cities.

引用

页码：129 / 137

页数：9

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