Modelling Air Pollution Crises Using Multi-agent Simulation

被引：8

作者：

Ghazi, Sabri ^{[1
]}

Dugdale, Julie ^{[2
,3
]}

Khadir, Tarek ^{[4
]}

机构：

[1] Univ Badji Mokhtar, Comp Sci Dept, POB 12, Annaba 23000, Algeria

[2] Univ Grenoble Alps, Lig, France

[3] Univ Agder, Agder, Norway

[4] Univ Badji Mokhtar, Comp Sci Dept, Lab Gest Elect Document, POB 12, Annaba 23000, Algeria

来源：

PROCEEDINGS OF THE 49TH ANNUAL HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES (HICSS 2016) | 2016年

关键词：

D O I：

10.1109/HICSS.2016.29

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper describes an agent based approach for simulating the control of an air pollution crisis. A Gaussian Plum air pollution dispersion model (GPD) is combined with an Artificial Neural Network (ANN) to predict the concentration levels of three different air pollutants. The two models (GPM and ANN) are integrated with a MAS (multi-agent system). The MAS models pollutant sources controllers and air pollution monitoring agencies as software agents. The population of agents cooperates with each other in order to reduce their emissions and control the air pollution. Leaks or natural sources of pollution are modelled as uncontrolled sources. A cooperation strategy is simulated and its impact on air pollution evolution is assessed and compared. The simulation scenario is built using data about Annaba (a city in North-East Algeria). The simulation helps to compare and assess the efficiency of policies to control air pollution during crises, and takes in to account uncontrolled sources.

引用

页码：172 / 177

页数：6

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