摘要
利用Matlab工具箱,对时序数据进行了两种不同形式的建模和预测。一是利用系统辨识方法来建立AR模型,利用所建模型进行预测;二是利用单隐层BP神经网络,对数据进行非线性拟合和预测。通过可视化,比较了两种方法的优劣。
Using Matlab Toolbox, two different ways were used to fit and to predict a model on time series data. One was using System- Identification- Toolbox to fit a model( simulated and predicted). Another was using BP- Network( one bidden- layer) to fit a model. The advantages and disadvantages were compared under the view condition
出处
《山东农业大学学报(自然科学版)》
CSCD
北大核心
2006年第3期471-476,共6页
Journal of Shandong Agricultural University:Natural Science Edition
关键词
时序分析
AR模型
MATLAB编程
BP神经网络
隐含层神经元数
Time series analysis, AR - model, Matlab programming, BP - Network, The number of neuron on the hidden -layer,To Predicts