A knowledge based approach for PM2.5 air pollution effects analysis

被引:0
|
作者
Oprea, Mihaela [1 ]
Liu, Hai-Ying [2 ]
机构
[1] Petr Gas Univ Ploiesti, Dept Automat Control Comp & Elect, Ploiesti, Romania
[2] NILU Norwegian Inst Air Res, Kjeller, Norway
关键词
knowledge base; decision support system; PM2.5 air pollution analysis; knowledge discovery technique; inductive learning; neural forecasting model; PARTICULATE MATTER; DECISION-SUPPORT; ENVIRONMENT;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The paper presents a knowledge based approach applied to air pollution effects analysis in the case of PM2.5 air pollutant which has potential significant negative effects on human health. The use of knowledge derived from various sources (e.g. literature, databases, questionnaires, human experts' experience, and decision tables) via manual, semiautomatic and automatic methods is proposed for a multi-parameters analysis of the PM2.5 air pollution episodes effects on vulnerable people such as children and elderly. Some measures to reduce the negative effects on human health are also proposed by our approach. The knowledge under the form of production rules is incorporated in a knowledge base that is used by the ROKIDAIR intelligent decision support system (ROKIDAIR DSS). The knowledge base coherence was verified with the expert systems generator, VP-Expert. The experimental data sets that were used are for some air pollution monitoring sites situated in the Ploiesti city and included in the Romanian National Air Quality Monitoring Network.
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页数:8
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