摘要
粗糙集无需提供问题所需处理的数据集合之外的任何先验信息,是一种通过知识约简,消除冗余数据的软计算方法;BP神经网络是一种通过自身的学习机制自动形成所要求的决策区域技术。综合了粗糙集和BP神经网络的各自优势,构建了一种新颖的葡萄病害分类模型。测试结果表明,所建模型对葡萄病害分类是行之有效的。
Rough set,without providing any prior information but the necessary data sets,is a soft computing method through reducing the original data to eliminate redundant data.BP neural network is a technique which automatically forms the required decision-making region through its own learning mechanism.Considering the advantages of rough set theory and BP neural network in information disposal,this paper constructs a novel classification model of grape diseases.The results show that the model of grape diseases is feasible and effective.
出处
《计算机工程与应用》
CSCD
2012年第29期239-242,248,共5页
Computer Engineering and Applications
基金
国家高技术研究发展计划(863)(No.2006AA100208-2)
西北农林科技大学科技创新项目支持
西北农林科技大学人才资金资助(No.01140409)
关键词
粗糙集
BP神经网络
葡萄病害
分类模型
rough set theory
BP neural network
grape diseases
classification model
