Air quality assessment using a weighted Fuzzy Inference System

Olvera-García, Miguel Ángel; Hernández, José Juan Carbajal; Sánchez-Fernández, Luis Pastor; Hernández-Bautista, Ignacio

doi:10.1016/j.ecoinf.2016.04.005

Cited by 57 publications

(18 citation statements)

References 28 publications

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“…Olvera-García et al proposed a novel assessment model utilizing fuzzy inference integrated with an analysis hierarchy process, contributing to a new air quality index. Simulation results illustrated that the presented air quality index provided a better evaluation than those in previous studies [16]. The aforementioned evaluation methods have no capability to take the quantification of evaluation factors and the randomness and fuzziness of hierarchy into consideration simultaneously, which makes evaluation results lack relative accuracy.…”

Section: Introductionmentioning

confidence: 91%

Research and Application of an Air Quality Early Warning System Based on a Modified Least Squares Support Vector Machine and a Cloud Model

Wang

Niu

Wang

2017

IJERPH

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The worsening atmospheric pollution increases the necessity of air quality early warning systems (EWSs). Despite the fact that a massive amount of investigation about EWS in theory and practicality has been conducted by numerous researchers, studies concerning the quantification of uncertain information and comprehensive evaluation are still lacking, which impedes further development in the area. In this paper, firstly a comprehensive warning system is proposed, which consists of two vital indispensable modules, namely effective forecasting and scientific evaluation, respectively. For the forecasting module, a novel hybrid model combining the theory of data preprocessing and numerical optimization is first developed to implement effective forecasting for air pollutant concentration. Especially, in order to further enhance the accuracy and robustness of the warning system, interval forecasting is implemented to quantify the uncertainties generated by forecasts, which can provide significant risk signals by using point forecasting for decision-makers. For the evaluation module, a cloud model, based on probability and fuzzy set theory, is developed to perform comprehensive evaluations of air quality, which can realize the transformation between qualitative concept and quantitative data. To verify the effectiveness and efficiency of the warning system, extensive simulations based on air pollutants data from Dalian in China were effectively implemented, which illustrate that the warning system is not only remarkably high-performance, but also widely applicable.

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Section: Introductionmentioning

confidence: 91%

Research and Application of an Air Quality Early Warning System Based on a Modified Least Squares Support Vector Machine and a Cloud Model

Wang

Niu

Wang

2017

IJERPH

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“…For extremely high and good concentrations, trapezoidal functions are selected, using the minimal value when a pollutant is considered. Whereas the triangular function was selected when the center of the range can be considered as a neutral point in the intermedia levels [28].…”

Section: Membership Function and Fuzzy Relation Matrixmentioning

confidence: 99%

Application of Fuzzy Synthetic Evaluation for the Air Quality Assessment in the Selected Cities of China

Yu¹

2018

IJEPP

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In this research, the air quality of six selected cities in China are evaluated according to the air monitoring data. Air pollutants including SO 2 , NO 2 , PM 10 , PM 2.5 , CO and O 3 are chose as air quality indicators and compared with the ambient air quality standards of China (GB3095-2012). Using the fuzzy theory, the fuzzy synthetic evaluation model are constructed, and the air quality of the six selected cities are evaluated. Results show that the air quality of Beijing, Tianjing, Taiyuan, Dalian, Wuhan and Kunming in the year of 2014 belong to the second level in the ambient air quality standards of China (GB3095-2012). The air quality of the cities also obey the order: Kunming > Dalian > Taiyuan > Beijing > Wuhan > Tianjing. It seems that PM 2.5 and PM 10 are the main pollutants in the atmosphere of the six selected cities. These results can help the environmental regulators to make the right policy in environmental management.

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“…As a result of the analysis of existing studies [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16], one can conclude that for the development of methodology of quantitative assessment of the processes of quality management system of enterprises, it is necessary to look for dependencies, which would take into account the above mentioned drawbacks.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…There are no similar systems at various enterprises [6] because their complexity depends on the type of manufactured products or services, the scope and structure of enterprises, the processes that are performed at an enterprise [7], on personnel qualification and many other factors.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

See 1 more Smart Citation

Development of qualimetric approaches to the processes of quality management system at enterprises according to international standards of the ISO 9000 series

Trisch

Gorbenko

Доценко

et al. 2016

EEJET

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Air quality assessment using a weighted Fuzzy Inference System

Cited by 57 publications

References 28 publications

Research and Application of an Air Quality Early Warning System Based on a Modified Least Squares Support Vector Machine and a Cloud Model

Research and Application of an Air Quality Early Warning System Based on a Modified Least Squares Support Vector Machine and a Cloud Model

Application of Fuzzy Synthetic Evaluation for the Air Quality Assessment in the Selected Cities of China

Development of qualimetric approaches to the processes of quality management system at enterprises according to international standards of the ISO 9000 series

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