Modeling of Nonlinear Autoregressive Neural Network for Multi-Step Ahead Air Quality Prediction

被引：1

作者：

Pasic, Mirza ^{[1
]}

Bijelonja, Izet ^{[1
]}

Kadric, Edin ^{[1
]}

Bajric, Hadis ^{[1
]}

机构：

[1] Univ Sarajevo, Mech Engn Fac Sarajevo, Vilsonovo Setaliste 9, Sarajevo, Bosnia & Herceg

来源：

TEM JOURNAL-TECHNOLOGY EDUCATION MANAGEMENT INFORMATICS | 2020年 / 9卷 / 03期

关键词：

NARX-SP; neural network; air pollutant concentration; meteorological parameters; POLLUTION;

D O I：

10.18421/TEM93-03

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper five neural network models were developed using NARX-SP neural network type in order to predict air pollutants concentrations (SO2, PM10, NO2, O-3 and CO) for the 72nd hour ahead for Sarajevo. Hourly values of air pollutants concentrations and meteorological parameters (air temperature, pressure and humidity, wind speed and direction) for Sarajevo were used. Optimal model was selected based on the values of R (2), MSE and the complexity of models. Optimal neural network model can predict air pollutants concentrations for the 72nd hour ahead with high accuracy, as well as for all hours up to 72nd hour.

引用

页码：852 / 861

页数：10

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