计算机工程与应用Issue(9)：236-239,4.DOI:10.3778/j.issn.1002-8331.1109-0120
一种 BP 神经网络机场噪声预测模型
Airport noise prediction model based on BP neural network
摘要
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 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.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)Key words
Back Propagation(BP)neural network/airport noise/prediction model/Noise-Power-Distance(NPD)分类
信息技术与安全科学引用本文复制引用
杜继涛,张育平,徐涛..一种 BP 神经网络机场噪声预测模型[J].计算机工程与应用,2013,(9):236-239,4.基金项目
国家自然科学基金重点课题(No.61139002) （No.61139002）
中国民用航空局科技项目(No.MHRD201006,No.MHRD201101) （No.MHRD201006,No.MHRD201101）
