基于CDAN技术与BP算法的棉花病虫害入侵检测-预报系统模型  

The model of cotton intrusion detection system based on the CDAN technology and BP algorithm

作　　者：巩林明[1,2] 张振国[1] 

机构地区：[1]陕西科技大学,陕西西安71000 [2]石河子大学,新疆石河子83200

出　　处：《广东农业科学》2009年第7期228-230,236,共4页Guangdong Agricultural Sciences

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.

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 

分 类 号：TP3-05[自动化与计算机技术—计算机科学与技术] S126[农业科学—农业基础科学]