Risk assessment of particulate matters in a dentistry school using fuzzy inference systems. (February 2018)

• Record Type: Journal Article
• Authors: Jamshidi, Hamid Reza; Karimi, Ali; Haghshenas, Mahin
• Is Part Of: Measurement. Volume 116(2018)
• Page Start: 257
• Page End: 263
• Publication Date: 2018-02
• Subjects: Fuzzy inference system -- Dental school -- Particulate matters -- Risk assessment; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2017.11.010
• Languages: English
• ISSNs: 0263-2241

Abstract

Graphical abstract: Highlights: Fuzzy approach allows flexible results for prediction of health risk levels of particulate pollution in dentistry school. Surfaces graph shows the impact and relationship between different groups of particulate matters very well. Sensitivity of this approach for particulate matters risk assessment better than standards. The outputs of fuzzy approach are the combination of input variables. Abstract: The fuzzy logic approach used to estimate the health risk of suspended dust in different parts of a dentistry school. Three input variables, including PM2.5, PM10 and TSP, and health risk level as the output variable were fuzzed using a fuzzy inference system. Trapezoidal and Triangular membership function were used to graphically defined the outputs (very low, low, moderate, high and very high) in fuzzy sets. The greatest concentrations of particle matters in general orthodontics with 15.9 mg/m 3 of TSP and 7.6 mg/m 3 of PM10 and after which special orthodoxies TSP (13.5 mg/m 3 ) and PM10 (7.1 mg/m 3 ) in all the parts. Also, surface graphs illustrated the relationship between PM2.5, PM10 and TSP. Fuzzy inference system as a novel approach was used for prediction of health risk levels of particulate pollution in dentistry school. Also, this method can be used effectively in other workplace like hospital and health care facilities.