A Fuzzy Soft Model for Haze Pollution Management in Northern Thailand

In this article, we propose fuzzy soft models for decision making in the haze pollution management. The main aims of this research are (i) to provide a haze warning system based on real-time atmospheric data and (ii) to identify the most hazardous location of the study area. PM10 is used as the seve...

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Main Author: Parkpoom Phetpradap
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Advances in Fuzzy Systems
Online Access:http://dx.doi.org/10.1155/2020/6968705
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author Parkpoom Phetpradap
author_facet Parkpoom Phetpradap
author_sort Parkpoom Phetpradap
collection DOAJ
description In this article, we propose fuzzy soft models for decision making in the haze pollution management. The main aims of this research are (i) to provide a haze warning system based on real-time atmospheric data and (ii) to identify the most hazardous location of the study area. PM10 is used as the severity index of the problem. The efficiency of the model is justified by the prediction accuracy ratio based on the real data from 1st January 2016 to 31st May 2016. The fuzzy soft theory is modified in order to make models more suitable for the problems. The results show that our fuzzy models improve the prediction accuracy ratio compared to the prediction based on PM10 density only. This work illustrates a fuzzy analysis that has the capability to simulate the unknown relations between a set of atmospheric and environmental parameters. The study area covers eight provinces in the northern region of Thailand, where the problem severely occurs every year during the dry season. Seven principle parameters are considered in the model, which are PM10 density, air pressure, relative humidity, wind speed, rainfall, temperature, and topography.
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institution Kabale University
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language English
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spelling doaj-art-2325e241e0d54c9dbdaca0cfc951b9c52025-02-03T06:45:47ZengWileyAdvances in Fuzzy Systems1687-71011687-711X2020-01-01202010.1155/2020/69687056968705A Fuzzy Soft Model for Haze Pollution Management in Northern ThailandParkpoom Phetpradap0Department of Mathematics, Faculty of Science, Chiang Mai University, Chiang Mai 50200, ThailandIn this article, we propose fuzzy soft models for decision making in the haze pollution management. The main aims of this research are (i) to provide a haze warning system based on real-time atmospheric data and (ii) to identify the most hazardous location of the study area. PM10 is used as the severity index of the problem. The efficiency of the model is justified by the prediction accuracy ratio based on the real data from 1st January 2016 to 31st May 2016. The fuzzy soft theory is modified in order to make models more suitable for the problems. The results show that our fuzzy models improve the prediction accuracy ratio compared to the prediction based on PM10 density only. This work illustrates a fuzzy analysis that has the capability to simulate the unknown relations between a set of atmospheric and environmental parameters. The study area covers eight provinces in the northern region of Thailand, where the problem severely occurs every year during the dry season. Seven principle parameters are considered in the model, which are PM10 density, air pressure, relative humidity, wind speed, rainfall, temperature, and topography.http://dx.doi.org/10.1155/2020/6968705
spellingShingle Parkpoom Phetpradap
A Fuzzy Soft Model for Haze Pollution Management in Northern Thailand
Advances in Fuzzy Systems
title A Fuzzy Soft Model for Haze Pollution Management in Northern Thailand
title_full A Fuzzy Soft Model for Haze Pollution Management in Northern Thailand
title_fullStr A Fuzzy Soft Model for Haze Pollution Management in Northern Thailand
title_full_unstemmed A Fuzzy Soft Model for Haze Pollution Management in Northern Thailand
title_short A Fuzzy Soft Model for Haze Pollution Management in Northern Thailand
title_sort fuzzy soft model for haze pollution management in northern thailand
url http://dx.doi.org/10.1155/2020/6968705
work_keys_str_mv AT parkpoomphetpradap afuzzysoftmodelforhazepollutionmanagementinnorthernthailand
AT parkpoomphetpradap fuzzysoftmodelforhazepollutionmanagementinnorthernthailand