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Identification of factors affecting noise levels by using data mining and design of experiments analysis techniques: A novel experimental approach

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The sounds that are high enough, which negatively affect our understanding, are called noise. Although students are one of the main sources of noise at schools, noise adversely affects students' success. Schools' acoustics and the time when the noise measurement is made are usually considered to be other reasons for noise. In this study, noise measurements are collected in several of a metropolitan city's primary and secondary schools, and factors that affect noise significantly are investigated using 2(3) full factorial experimental designs. In addition, school teachers' perception of noise is analyzed by the Apriori algorithm. Results indicate that noise values exceed the limit values set by the WHO and noise regulations currently in effect in Turkey. Also, the schools with no acoustic insulation were noisier than those with minimum insulation. From the Apriori analysis, it is concluded that female teachers are more sensitive than male teachers about noise annoyance.

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School-children, Performance, Noise, Noise pollution, Experimental design, Full factorial experiments, Data mining, Science & technology, Technology, Acoustics

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