| 来源类型 | Article |
| 规范类型 | 其他 |
| DOI | 10.1016/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 |
| URL | http://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. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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