摘要
为了提高棉花生产的信息化和棉花病虫害预报的效率与智能性,针对棉花病虫害入侵产生因素的多维性,对棉花叶面信息表现的时序、棉花叶面的状态在时间和空间域中表现出的紧密相关性进行了分析,把人工神经网中的BP神经网络算法和信息安全领域中的入侵检测技术CDAN引进来,构造成基于CDAN技术与BP神经网络的棉花病虫入侵检测-预报系统。
In order to enhance the information of the cotton production and the efficiency and intelligence of agricultural plant disease forecast, in term of the multi-dimensional factors caused the disease and the insect pest intrusion to the cotton, it carried on the analysis to the time thread of the information displayed by the cotton leaves and the closed relevance between the time and the spatial domain of the leaves. By introducing the BP neural network algorithm and the CDAN technology of intrusion detection from the domain of the information, made this system.
出处
《广东农业科学》
CAS
CSCD
北大核心
2009年第7期228-230,236,共4页
Guangdong Agricultural Sciences
关键词
病虫入侵检测
BP神经网络
异常检测
规则库
门限检测
时序
pest and diseases intrusion detection
BP neural network
anomaly detection
rule set
threshold detection
time thread
