| 一种改进的三维流场数据可视化方法 |
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| 引用本文： | 李春鑫,彭认灿,高占胜,王海波.一种改进的三维流场数据可视化方法[J].武汉大学学报(信息科学版),2017,42(6):744-748. |
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| 作者姓名： | 李春鑫 彭认灿 高占胜 王海波 |
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| 作者单位： | 1.海军大连舰艇学院测绘科学与技术博士后科研流动站, 辽宁 大连, 116018 |
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| 基金项目： | 中国博士后科学基金2014M552659中国博士后科学基金2015T81109国家自然科学基金41471380国家自然科学基金41171349 |
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| 摘 要： | 针对三维流场数据可视化容易出现的显示混乱问题，提出一种三维流场可视化自适应方法。该方法引入模糊支持向量机对流场特征进行分类预处理，并提出一种改进的线积分卷积算法，该算法利用模糊支持向量机得到的隶属度自适应生成Sobol稀疏噪声，避免当噪声过于稠密时产生重叠现象，而当噪声过于稀疏时漏掉流场重要的细节信息。通过多组流场三维可视化仿真实验的比较与分析，验证了本文方法的有效性。
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| 关 键 词： | 模糊支持向量机 线积分卷积 流场 可视化 |
| 收稿时间： | 2015-04-30 |
An Improved Legible Method for Visualizing 3D Flow Field |
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| Affiliation: | 1.Postdoctoral Programme of Surveying and Mapping, Dalian Naval Academy, Dalian 116018, China2.Dept. of Hydrography and Cartography, Dalian Naval Academy, Dalian 116018, China3.Dept. of Navigation, Dalian Naval Academy, Dalian 116018, China |
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| Abstract: | To deal with the problem of confused display in 3D visualization of a flow field, an adaptive visualization method for flow fields is put forward. Due to the complicated feature in flow field, a fuzzy support vector machine is applied to describe and cluster the flow field features. To resolve the overlapping effects caused by excessive noise or omission of details caused when noise is removed, an improved line integral convolution algorithm is also presented. In the improved algorithm a fuzzy membership function obtained by fuzzy support vector machine generates sparse noise adaptively Experimental results illustrate the efficiency of the method. |
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