摘要
针对传统专家系统自学能力差的特点,以实现基于W eb的智能葡萄病害诊断系统为目标,研究了26种葡萄常见病害模糊隶属度的表示方法及模糊BP神经网络模型,采用Java与M atlab混合编程方法实现了该系统的葡萄病害诊断功能。试验结果表明,该系统病害诊断正确率达90.9%,且能在W eb上运行,便于推广和使用。
Aimed at the weak self-learning ability of traditional expert system, the expression method for fuzzy subordination and the mode of fuzzy back-propagation artificial neural network for 26 kinds of common grape diseases was studied, so as to realize a web based intelligent grape disease diagnosis system, which was implemented by JAVA and MATLAB. The system can be popularized easily as it is designed to be run online, and experimental results show that the system can diagnose grape diseases with the accuracy of 90.9%. The analyses of the diagnosis results of typical examples indicate that this system has stable reliability, can simulate the expert diagnosis process adequately, and can improve the diagnosis efficiency greatly.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2006年第9期144-147,共4页
Transactions of the Chinese Society of Agricultural Engineering
关键词
葡萄病害
模糊神经网络
诊断
模糊隶属度
grape diseases
fuzzy neural network
diagnosis
fuzzy subordination
