基于多智能体的PM10危机高峰模拟：阿尔及利亚东北部安纳巴市的应用
Modelling PM10 Crisis Peaks Using Multi-Agent based Simulation: Application to Annaba City, North-East Algeria
摘要：
本文描述了一种控制PM10（颗粒物）危机峰值的MAS（多智能体系统）仿真方法。扩散模型与人工神经网络（ANN）一起用于预测PM10浓度水平。分散和人工神经网络模型集成到一个MAS系统。PM10源控制器被建模为软件代理。MAS由多个代理组成，这些代理相互合作以减少排放并控制空气污染峰值。不同的控制策略进行了模拟和比较使用的数据从安纳巴（阿尔及利亚东北部）。该模拟器有助于比较和评估控制PM10峰值的政策的效率。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
