Urban road network modeling and real-time prediction based on householder transformation and adjacent vector

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作者：
Department of Automation and TNList, Tsinghua University, Beijing 100084, China [1 ]
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来源：
Lect. Notes Comput. Sci. | 1600年 / PART 3卷 / 899-908期
关键词：
Compendex;
D O I：
6th International Symposium on Neural Networks, ISNN 2009
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学科分类号：
摘要：
Roads and streets
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