基于支持向量机的翠冠梨大小等级评定模型构建  

Construction of Size Grading Model for Cuiguan Pear Based on Support Vector Machine

作　　者：刘现[1] 郑华伟 Liu Xian;Zheng Huawei(Digital Agriculture Research Institute,Fujian Academy of Agricultural Sciences,Fuzhou,China;School of Computer Science and Technology,Fujian Agriculture and Forest University,Fuzhou,China)

机构地区：[1]福建省农业科学院数字农业研究所,福建福州 [2]福建农林大学计算机与信息学院,福建福州

出　　处：《科学技术创新》2023年第24期221-224,共4页Scientific and Technological Innovation

基　　金：福建省农业科学院自由探索科技创新项目“基于大数据的翠冠梨智能分级模型构建”(ZYTS202234);福建省农业科学院科技创新团队“智慧农业科技创新团队”(CXTD2021013-1);福建省农业科学院科技创新团队“南方丘陵农情监测科技创新团队”(CXTD2021012-3)。

摘　　要：为了提高翠冠梨大小检测及等级评定的智能化程度与效率,基于支持向量机构建了一套翠冠梨大小等级评定模型。利用自主研制的图像采集系统试验平台构建翠冠梨大小分类图像数据集,使用支持向量机算法构建翠冠梨大小等级评定模型,将该模型与贝叶斯分类和决策树算法所构建的模型进行对比,评估其分类效果和性能。实验结果表明,综合考虑模型分类准确率和运行时间,基于支持向量机的翠冠梨大小等级评定模型相较于其他两种算法所构建的模型是最佳的。本研究结果可为翠冠梨大小分级方法提供技术参考。In order to improve the intelligence and efficiency of Cuiguan pear size detection and grade evaluation,a set of Cuiguan pear size grade evaluation model was built based on Support Vector Machine.On the self-developed image acquisition system experimental platform,a dataset of Cuiguan pear size classification images were built.Based on the images,the Support Vector Machine algorithm was used to construct a set of Cuiguan pear size grade evaluation model.To evaluate its classification performance and efficiency,the model was compared with models constructed by Bayesian classification and Decision Tree algorithms.The experimental results show that,considering the classification accuracy and running time of the model,Cuiguan pear size grade evaluation model constructed by Support Vector Machine was the best compared to the other two algorithms.The results of this study can provide a technical reference for the size grading method of Cuiguan pear.

关 键 词：翠冠梨 大小 支持向量机 贝叶斯 决策树 模型 

分 类 号：S661.2[农业科学—果树学]