| 基于遗传-小波神经网络的短时交通量预测 |
| |
| 引用本文： | 黄恩洲.基于遗传-小波神经网络的短时交通量预测[J].海南大学学报(自然科学版),2014(1):55-59. |
| |
| 作者姓名： | 黄恩洲 |
| |
| 作者单位： | 福建工程学院交通运输系,福建福州350108 |
| |
| 基金项目： | 国家自然科学基金（61304210）;福建工程学院科研发展基金（GY-211057）;福建省教育厅A类基金（JA11192） |
| |
| 摘 要： | 针对短时交通量的高度非线性,提出一种基于遗传-小波神经网络的预测方法.该方法以前馈多层感知器的神经网络拓扑结构为基础,选择Morlet母小波基函数作为隐含层激活函数,以最简化结构概念进行网络泛化,并将误差反向传播,经遗传算法对网络连接权值修正.实例证明,该方法预测精度高,预测速度较快,能够满足实际工程的要求.
|
| 关 键 词： | 短时交通量 小波 神经网络 遗传算法 |
Short-term Traffic Volume Forecasting Based on Genetic-wavelet Neural Network |
| |
| HUANG En-zhou.Short-term Traffic Volume Forecasting Based on Genetic-wavelet Neural Network[J].Natural Science Journal of Hainan University,2014(1):55-59. |
| |
| Authors: | HUANG En-zhou |
| |
| Institution: | HUANG En-zhou ( Department of Traffic and Transportation, Fujian University of Technology, Fuzhou, 350108, China) |
| |
| Abstract: | In the report, aimed at advanced nonlinearity of short-term traffic volume, a kind of forecasting meth- od named genetic-wavelet neural network was proposed, which is based on topological structure of multilayer feed-forward perceptions （MLPs）, and in which Morlet mother wavelet function is selected to be active function of hide-layer. The network was generalized by minimization feature structure （MFS） concept, and output error was back propagated to genetic algorithm module to optimize connection weights of network. The forecasting ex- ample indicated that the accuracy ~,d ,~ .c .t. 1_ ~ |
| |
| Keywords: | short-term traffic volume wavelet neural network genetic algorithm |
| 本文献已被 CNKI 维普 等数据库收录！ |
|
