CAJ | 학술논문

机场噪声预测对机场噪声控制、航班计划制定和机场规划设计具有十分重要的作用.现有的机场噪声预测模型都是以飞机的噪声距离曲线(NPD 曲线)为核心,用相应的数学模型将其修正至与具体机场的特定环境条件相关的噪声传播模型,存在预测成本高和误差大的缺点.针对这种情况,提出一种使用 BP 神经网络利用机场噪声历史监测数据进行NPD 曲线修正计算方法,从而建立适用于特定机场环境条件的机场噪声预测模型.实验表明,在特定机场的特定环境条件下,允许误差为0.5 dB 时,该模型预测准确率高达91.5%以上,具有预测成本小、准确度高的特点.
궤장조성예측대궤장조성공제、항반계화제정화궤장규화설계구유십분중요적작용.현유적궤장조성예측모형도시이비궤적조성거리곡선(NPD 곡선)위핵심,용상응적수학모형장기수정지여구체궤장적특정배경조건상관적조성전파모형,존재예측성본고화오차대적결점.침대저충정황,제출일충사용 BP 신경망락이용궤장조성역사감측수거진행NPD 곡선수정계산방법,종이건립괄용우특정궤장배경조건적궤장조성예측모형.실험표명,재특정궤장적특정배경조건하,윤허오차위0.5 dB 시,해모형예측준학솔고체91.5%이상,구유예측성본소、준학도고적특점.
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 pre-diction 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 environ-mental 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.