| 基于数据挖掘技术与支持向量机的目标识别研究 |
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| 引用本文： | 段纪军,陈琳,王海燕,田娜. 基于数据挖掘技术与支持向量机的目标识别研究[J]. 计算机与数字工程, 2004, 32(6): 41-44,72 |
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| 作者姓名： | 段纪军 陈琳 王海燕 田娜 |
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| 作者单位： | 华中光电技术研究所,武汉,430074;西北工业大学航海学院,西安,710072 |
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| 摘 要： | 提出了基于数据挖掘技术及基于支持向量机的两种水中目标识别方法，分别藉助目标噪声特征量提取和模式识别算法以及支持向量及二次规划算法，对比性地研究了不同工况下三类目标的分类识别效果。其方法和结果对水中目标识别有较好的参考价值。
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| 关 键 词： | 数据挖掘 支持向量机 目标识别 聚类分析 |
Research on Target Recognition Based on Data Mining Technique and Support Vector Machine |
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| Duan Jijun ) Chen Lin ) Wang Haiyan ) Tian Na ). Research on Target Recognition Based on Data Mining Technique and Support Vector Machine[J]. Computer and Digital Engineering, 2004, 32(6): 41-44,72 |
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| Authors: | Duan Jijun ) Chen Lin ) Wang Haiyan ) Tian Na ) |
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| Affiliation: | Duan Jijun 1) Chen Lin 1) Wang Haiyan 2) Tian Na 2) |
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| Abstract: | This paper deals with the underwater target recognition approach based on data mining technique and support vector machine. By means of target noise characteristic abstraction, pattern recognition algorithm, support vector machine and quadratic programming algorithm, the paper completed the clustering analysis of three kinds of targets at different ambient background situation. Experiment results indicate that this method has good performance and robustness, and the recognition result is satisfactory for practical use. |
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| Keywords: | data mining support vector machine target recognition clustering analysis |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
