关键词: 反向传播（BP）神经网络, 机场噪声, 预测模型, 噪声距离曲线（NPD）

Abstract: Airport noise prediction plays an important role in airport noise controlling, flight planning and airport designing. The airport noise prediction models?are usually built based on aircraft noise distance curve（NPD）, and the NPD curves are little by little revised to the noise propagation model under the specific airport environmental conditions by using a variety of mathematical models. In this way, there are shortcomings of the high cost and great prediction error. This paper presents an airport noise prediction model for particular airport environmental conditions. The proposed model applies BP neural network and history data of the airport noise monitoring to modifying the NPD curves. Experiment results show that in particular specific airport environmental conditions, the accuracy rate of noise prediction is more than 91.5% in the case of ±0.5 dB error. The proposed model has the features of lower cost and high accuracy.

Key words: Back Propagation（BP） neural network, airport noise, prediction model, Noise-Power-Distance（NPD）