计算机应用研究2011，Vol.28Issue(5)：1961-1964,4.DOI:10.3969/j.issn.1001-3695.2011.05.104
一种非线性降维算法在组合预测模型中的应用
Application of nonlinear dimensional reduction algorithm in combination predictive model
摘要
Abstract
Aiming at the features of video sequences, i.e., the higher dimension, larger relativity of frame, and complex trajectories, this paper proposed applying the reduction algorithm of LLE nonlinear dimensionality to video processing.In particularly,this paper focused on how to utilize the above algorithm to predictively update the model of moving objective tracking.Because the single-step prediction could not guarantee the accuracy in the complex environment with part or the whole hided,this paper integrated the time series model with BP neural network to achieve multi-step prediction, which could overcome the shortcoming of time series model.The experiment results show that this proposed method can attain better accuracy and robustness for moving object tracking.关键词
局部线性嵌入降维算法/时间序列模型/反向传播神经网络/多步预测Key words
LLE algorithm/ time series model/ BP neural network/ multi-step prediction分类
信息技术与安全科学引用本文复制引用
吴孟俊,刘建平,牛玉刚..一种非线性降维算法在组合预测模型中的应用[J].计算机应用研究,2011,28(5):1961-1964,4.基金项目
国家自然科学基金资助项目(61074041) （61074041）
上海市教委科技创新重点资助项目(09ZZ60) （09ZZ60）
上海市重点学科资助项目(B504) （B504）
