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来源类型Article
规范类型其他
DOI10.1016/j.atmosenv.2012.03.033
Defining a nonlinear control problem to reduce particulate matter population exposure.
Carnevale C; Finzi G; Pisoni E; Volta M; Wagner F
发表日期2012
出处Atmospheric Environment 55: 410-416
出版年2012
语种英语
摘要In this paper a multi-objective nonlinear approach to control air quality at a regional scale is presented. Both economic and air quality sides of the problem are modeled through artificial neural network models. Simulating the complex nonlinear atmospheric phenomena, they can be used in an optimization routine to identify the efficient solutions of a decision problem for air quality planning. The methodology is applied over Northern Italy, an area in Europe known for its high concentrations of particulate matter. Results illustrate the effectiveness of the approach assessing the nonlinear chemical reactions in an air quality decision problem.
主题Mitigation of Air Pollution (MAG) ; Air Quality & ; Greenhouse Gases (AIR)
关键词Multi-objective optimization Year of Lost Life Emission control Neural networks GAINS model
URLhttp://pure.iiasa.ac.at/id/eprint/9989/
来源智库International Institute for Applied Systems Analysis (Austria)
引用统计
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/129568
推荐引用方式
GB/T 7714
Carnevale C,Finzi G,Pisoni E,et al. Defining a nonlinear control problem to reduce particulate matter population exposure.. 2012.
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