| 胡杏花,朱谷昌.基于知识发现和决策规则的遥感影像分类研究——以北京市为例[J].矿产勘查,2019,(11):2758-2762 |
| 基于知识发现和决策规则的遥感影像分类研究——以北京市为例 |
| Research on remote sensing image classification based on knowledge discovery and decision rules:Taking Beijing as an example |
| 投稿时间：2019-09-15 |
| DOI： |
| 中文关键词: 影像分类 知识发现 决策规则 专家分类 知识库 |
| 英文关键词: image classification,knowledge discovery,decision rules,expert classification, knowledge base |
| 基金项目: |
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| 摘要点击次数: 1954 |
| 全文下载次数: 622 |
| 中文摘要: |
| 通过对遥感影像的非监督分类、监督分类和专家分类进行机理分析,提出基于知识发现和决策规则的专家知识改进分类精度的技术方案,并以北京市为例,开展对TM遥感影像的非监督分类、监督分类和专家分类的对比分析。专家分类方法由于总结了某一领域内知识发现和决策规则,可容纳更多信息,可以包括各种所需的或可获取的信息,可按某种可信度进行不确定性推理,大幅提高了遥感影像分类精度。 |
| 英文摘要: |
| By analyzed the mechanism of unsupervisory classification, supervision classification and expert classification of remote sensing image, presented a technical scheme for improving classification accuracy of expert knowledge based on knowledge discovery and decision rules, and Taked Beijing as an example, carried out a comparative analysis of unsupervised classification, supervised classification and expert classification of TM remote sensing images. The results showed that the expert classification method which summarized the knowledge discovery and decision rules in a certain field accommodated more information,included all kinds of required or available information,an be inferred with uncertainty according to some kind of credibility, and greatly improved the classification accuracy of remote sensing images. |
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