6533b83afe1ef96bd12a781a

RESEARCH PRODUCT

Modelling PM10 Crisis Peaks Using Multi-agent Based Simulation: Application to Annaba City, North-East Algeria

Julie DugdaleJulie DugdaleSabri GhaziTarek Khadir

subject

Environmental modellingEconomyMeteorologyArtificial neural networkSoftware agentMulti-agent systemAir pollutionmedicineEnvironmental scienceStatistical dispersionNorth eastmedicine.disease_causeAir quality index

description

The paper describes a MAS (multi-agent system) simulation approach for controlling PM10 (Particulate Matter) crisis peaks. A dispersion model is used with an Artificial Neural Network (ANN) to predict the PM10 concentration level. The dispersion and ANN models are integrated into a MAS system. PM10 source controllers are modelled as software agents. The MAS is composed of agents that cooperate with each other for reducing their emissions and control the air pollution peaks. Different control strategies are simulated and compared using data from Annaba (North-East Algeria). The simulator helps to compare and assess the efficiency of policies to control peaks in PM10.

yearjournalcountryeditionlanguage
2015-01-01
https://doi.org/10.1007/978-3-319-24399-3_6