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Noise generated by air traffic is one of the leading problems in urban areas in the world. That is why the measures for reducing the noise generated by air traffic are today the subject of constant improvement, extensive research, and standardization. Monitoring and predicting air traffic noise levels represent an important factor in quality control and noise management. In order to reduce the noise level in the vicinity of Mitiga International Airport (Tripoli) in Libya, the aim of this paper is to assess the noise emission levels before and after the introduction of certain measures to reduce airborne noise, as well as to predict the noise level at the analyzed area. The method of interpolation in the Geographic Information System (GIS) was used to graphically represent the spatial distribution of noise emissions in the study area, and by applying zonal statistics deviations from the allowable values for each control grid were calculated. The obtained results showed that the application of certain measures has a great impact on reducing noise levels on controlled grids. Finally, the reliability of noise level prediction was successfully assessed using the artificial neural network (ANN) method.
Nasr et al. (Fri,) studied this question.