改进的BP模型在噪声预测中的应用

交通噪声作为主要的城市噪声污染,分析预测交通噪声对管理规划城市交通和减少噪声污染具有重要意义。通过分析道路交通噪声的各项影响因子,并针对BP算法的不足,提出一种基于遗传算法与神经网络相结合的道路噪声预测模型。用武汉市道路噪声实测数据进行实验,验证了该模型的高精度和实用性。

Application of Improved BP Neural Network in Noise Forecasts

Analyzing and forecasting traffic noise,which has been a major urban noise pollution,plays a key role in managing urban transport and reducing noise pollution.Through analyzing factors of traffic noise and the disadvantage of BP algorithm,we present a noise prediction model based on neural networks and Genetic algorithm.Furthermore,the model is successfully applied to noise prediction of Wuhan.The results show that the precision of the model is accurate.