A study on time series prediction model based on CRBM algorithm(基于CRBM算法的时间序列预测模型研究)
针对受限玻尔兹曼机(restricted Boltzmann machines,RBM)算法对时序数据预测存在抽取抽象特征向量能力较差和梯度下降能力有限的问题,基于CRBM(conditional restricted Boltzmann machines)算法以及信念网络(deep belief network,DBN)模型,构建了 一种非线性的CRBM-DBN深度学习模型,并采用高斯分布处理输入特征值和对比散度抽样,用于预测时序数据.实验以浙江省近岸海域赤潮时序数据作为输入特征值,讨论该模型的深度及参数选取,并与经典的深度学习模型RBM、DAE和浅层学习中的BP神经网络进行对比,实验验证C...
Main Authors: | ZHOUXiaoli(周晓莉), ZHANGFeng(张丰), DUZhenhong(杜震洪), CAOMinjie(曹敏杰), LIURenyi(刘仁义) |
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Format: | Article |
Language: | zho |
Published: |
Zhejiang University Press
2016-07-01
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Series: | Zhejiang Daxue xuebao. Lixue ban |
Subjects: | |
Online Access: | https://doi.org/10.3785/j.issn.1008-9497.2016.04.011 |
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