基于人工免疫系统的遥感图像分类研究

2011 IEEE International Conference on Computer Science and Automation Engineering Pub Date : 2011-06-10 DOI:10.1109/CSAE.2011.5952734

X. Qin

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引用次数: 0

摘要

在分析负选择算法缺点的基础上，提出了一种基于人工免疫系统的双向选择算法。对训练样本集采用克隆选择和突变算法，得到成熟抗体集。然后利用成熟抗体集对遥感图像进行分类。结果表明，该算法优于传统的最大似然分类。其准确率达到87.4%。

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Study on remote sensing image classification based on artificial immune system

On the base of analyzing the disadvantages of the negative selection algorithm, a bidirectional selection algorithm based on artificial immune system is presented. Clone selection and mutation algorithms are used on the training sample set to obtain mature antibody set. Then the mature antibody set can be used to classify the remote sensing image. It is demonstrated that this algorithm is superior to conventional maximum likelihood classification. Its accuracy reaches 87.4 percent.

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2011 IEEE International Conference on Computer Science and Automation Engineering

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