摘要
为探索蔬菜病害诊断的有效方法,研究采用模糊系统与神经网络相结合的方法,在对蔬菜病害症状进行合理划分的基础上,利用综合考虑症状特征及隶属度的术语统一描述输入向量构建方法,建立蔬菜病害模糊神经网络诊断模型。结果表明,输入向量构建方法有效地表达了病害诊断规律,诊断模型容错能力强,正确率达85.5%。
To explore the effective method for the diagnosis of vegetables diseases,through reasonable division of symptoms,using input vector construction method which contained characteristics of symptoms and membership grade,a vegetables disease diagnosis of fuzzy neural network model was constructed.The experimental results showed that the input vector construction method had effectively expressed the disease diagnosis rule,the model had strong fault tolerant ability,and the average diagnostic accuracy was 85.5%.
出处
《湖北农业科学》
北大核心
2013年第17期4224-4227,共4页
Hubei Agricultural Sciences
基金
国家现代农业科技城综合信息"三农"服务平台建设项目(PT01)
北京市自然科学基金项目(9093019)
北京农业科学院信息所创新基金项目(SJJ201203)
关键词
模糊神经网络
蔬菜
病害
诊断
fuzzy neural network
vegetable
disease
diagnosis
