计算机工程Issue(7)：141-145,5.DOI:10.3969/j.issn.1000-3428.2014.07.028
时空神经网络及其在机场噪声预测中的应用
Space-time Neural Network and Its Application in Airport Noise Prediction
摘要
Abstract
A new space-time neural network is proposed using the function expansion technique and the linear impulse response filtering theory in this paper. It consists of function expansion and linear delay pulse. Net input space is mapped into a high dimensional space by function expansion. Therefore, nonlinear mode in low dimensional space can be converted to linear mode in high dimensional space. Linear delay pulse is equivalent to the temporal linear impulse response filter, which is responsible for fitting linear model in space-time series. Space-time neural network fast learning algorithm is proposed by using Levenberg-Marquardt optimization method. Simulation results show that space-time neural network has the characteristics of fast convergence and high precision. Compared with Space-time Autoregressive Moving Average(STARMA) and multilayer perceptron neural network, the prediction accuracy of the space-time neural network is significantly improved.关键词
时空神经网络/函数链接人工神经网络/线性脉冲响应滤波/时空自相关移动平均模型/时空序列/机场噪声Key words
space-time neural network/Functional Link Artificial Neural Network(FLANN)/linear impulse response filtering/Space-time Autoregressive Moving Average(STARMA) model/space-time series/airport noise分类
信息技术与安全科学引用本文复制引用
王尚北,王建东,陈海燕..时空神经网络及其在机场噪声预测中的应用[J].计算机工程,2014,(7):141-145,5.基金项目
国家自然科学基金资助重点项目(61139002)；国家“863”计划基金资助重点项目(2012AA063301)。 （61139002）
