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当前位置: 首页 > 文章 > 基于支持向量机的昆虫数值化鉴定 中国农学通报 2014 (7) 286-291
Position: Home > Articles > Digital Insect Identification Based On Support Vector Machine Chinese Agricultural Science Bulletin 2014 (7) 286-291

基于支持向量机的昆虫数值化鉴定

作  者：
吴宏华;张红燕;陈渊
单  位：
湖南农业大学信息科学技术学院;湖南省植物病虫害生物学与防控重点实验室
关键词：
支持向量机;数值化鉴定;特征筛选;昆虫识别
摘  要：
为提高昆虫鉴定的准确度,基于支持向量机提出了一种新的计算机昆虫数值化鉴定方法,并应用于以前翅内部翅脉交点距离为数值特征的7种蝴蝶的鉴定。首先利用DrawWing软件对7种蝴蝶的翅脉交点坐标进行了自动获取,并计算各相邻交点之间的欧式距离;然后将每类样本与其他样本组成二分类模型;再对每一模型经支持向量机非线性特征筛选,去除无用或冗余特征值,并以保留特征构建最终分类器。7个预测模型的独立测试平均精度达98.64%,明显高于参比模型,表明新方法在昆虫鉴定领域具有较好的应用前景。
译  名：
Digital Insect Identification Based On Support Vector Machine
作  者：
Wu Honghua;Zhang Hongyan;Chen Yuan;College of Information Science and Technology,Hunan Agricultural University;Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests;
关键词：
support vector machine(SVM);;digital identification;;features filtering;;insect identification
摘  要：
Based on support vector machine(SVM), a novel method for digital insect identification was proposed, and applied in identifying seven species of butterflies with intersectional coordinates of venation in the internal of forewings. The basic principles were as follows: firstly, the intersectional coordinates of venations in the internal of seven species' forewings were obtained automatically by DrawWing which was a program for numerical description of insect wings. Secondly, binary model was composed by the each type of sample and other samples. Thirdly, the redundant features or unnecessary features were filtered by using support vector classification, and the retained features were used to construct the classification model. Accuracy of 7 prediction model was 98.64%, and higher than the reference model, that the new method of identification in the field of insect had a good prospect.

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