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应用于地物识别的改进轮转森林算法

DOI: 10.11834/jig.20111110

Keywords: 混合算法,径向基函数神经网络,轮转森林,特征变换

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Abstract:

针对数量激增、数据类型复杂的遥感影像,准确和具有普适性的分类是亟待解决的问题。提出一种轮转径向基函数神经网络模型应用于遥感影像的处理方法。通过对输入数据的特征变换,使特征总集变为多个子特征集,依据PCA(主成分分析)变换处理这些新的子特征集,将得到的系数用于改变训练样本,增加基分类器之间的差异度,提高分类精度。以扎龙湿地为研究对象将该算法与其他方法比较,结果显示本文方法能得到更准确的分类结果,而且具有较高的泛化精度以及较小的过学习现象。

References

[1]  Li Shijin,Tao Jian,Wan Dingsheng,et al.Content-based remote sensing image retrieval using co-training of multiple classifiers [J].Journal of Remote Sensing,2010,14(3): 500- 506.[李士进,陶剑,万定生,等.多分类器实例协同训练遥感图像检索[J].遥感学报,2010,14(3):500-506.]
[2]  Ye Bo,Wen Yumei,He Weihua.Gait recognition based on the fusion of multiple classifiers [J].Journal of Image and Graphics,2009,14(8): 1627-1637.[叶波,文玉梅,何卫华.多分类器信息融合的步态识别算法[J].中国图象图形学报,2009,14(8):1627-1637.]
[3]  Nicolas G P,Domingo O B.Boosting random subspace method [J].Neural Networks,2008,21(9): 1344-1362.
[4]  Ioannis P,Grigorios T,Ioannis V.Pruning an ensemble of classifiers via reinforcement learning [J].Neurocomputing,2009,72(7-9): 1900-1909.
[5]  Akhand M A H,Islam M M,Murase K.Progressive interactive training: a sequential neural network ensemble learning method [J].Neurocomputing,2009,73(1-3): 260-273.
[6]  Koen W D B,Kristof C,Dirk V P.Ensemble classification based on generalized additive models [J].Computational Statistics & Data Analysis.2010,54(6): 1535-1546.
[7]  Wang Yuanyuan,Li Jing.Analysis of feature selection and its impact on hyper-spectral data classification based on decision tree algorithm [J].Journal of Remote Sensing,2007,11(1):69-76.[王圆圆,李京.基于决策树的高光谱数据特征选择及其对分类结果的影响分析[J].遥感学报,2007,11(1):69-76.]
[8]  Juan J R,Kuncheva L I,Carlos J A.Rotation forest: a new classifier ensemble method [J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2006,28(10):1619-1630.
[9]  Liu Kunhong,Huang Deshuang.Cancer classi fication using rotation forest [J].Computers in Biology and Medicine,2008,38(5): 601-610.
[10]  Zhang Chunxia,Zhang Jiangshe.RotBoost: a technique for combining rotation forest and AdaBoost [J].Pattern Recognition Letters,2008,29(10): 1524-1536.
[11]  Leo B.Random forests [J].Machine Learning,2001,45(1): 5-32.
[12]  Blake C L,Merz C J.1998.UCI Repository of Machine Learning Databases.[DB/OL] (2010-03-01) [2010-03-12] http://www.ics.uci.Edu/~mlearn/MLR―epository.html.

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