A Fuzzy Soft Model for Haze Pollution Management in Northern Thailand. (11th March 2020)

• Record Type: Journal Article
• Authors: Phetpradap, Parkpoom
• Other Names: Sanz Jose A. Academic Editor.
• Is Part Of: Advances in fuzzy systems. Volume 2020(2020)
• Publication Date: 2020-03-11
• Subjects: Fuzzy systems -- Periodicals; Systèmes flous; Fuzzy systems; Periodicals; 511.313
• DOI: 10.1155/2020/6968705
• Languages: English
• ISSNs: 1687-7101

Abstract

Abstract : 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 1 st January 2016 to 31 st 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.