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基于权重自动调整神经网络的水稻病虫害诊断专家系统
引用本文:孙传恒,唐启义,唐洁,程家安,杨信廷.基于权重自动调整神经网络的水稻病虫害诊断专家系统[J].农业工程学报,2007,23(6):159-164.
作者姓名:孙传恒  唐启义  唐洁  程家安  杨信廷
作者单位:1. 浙江大学应用昆虫学研究所,杭州,310029;国家农业信息化工程技术研究中心,北京,100089
2. 浙江大学应用昆虫学研究所,杭州,310029
3. 国家农业信息化工程技术研究中心,北京,100089
基金项目:国家高技术研究发展计划(863计划)
摘    要:针对水稻病虫害诊断特点,从人工智能角度出发,提出了一种基于权重自动调整的神经网络水稻病虫害的知识组织方式。文章以15种常见水稻病虫害为例,通过对病虫害症状的特点和特征进行分类、抽象和编码,构建了基于权重自动调整的BP神经网络。利用神经网络和不确定性推理技术,对实例样本进行训练学习,并将权值数据作为知识库来进行诊断,并基于这种方法构建了水稻病虫害神经网络诊断专家系统。

关 键 词:水稻病虫害  专家系统  神经网络  权重
文章编号:1002-6819(2007)6-0159-06
收稿时间:2005/8/18 0:00:00
修稿时间:2005-08-182006-04-22

Rice pest insects and diseases diagnosis expert system based on weight self-adjustment artificial neural networks
Sun Chuanheng,Tang Qiyi,Tang Jie,Cheng Jia''an and Yang Xinting.Rice pest insects and diseases diagnosis expert system based on weight self-adjustment artificial neural networks[J].Transactions of the Chinese Society of Agricultural Engineering,2007,23(6):159-164.
Authors:Sun Chuanheng  Tang Qiyi  Tang Jie  Cheng Jia'an and Yang Xinting
Institution:Applied Entomology Institute, Zhejiang University, Hangzhou 310029, China;National Engineering Research Center for Information Technology in Agriculture, Beijing 100089, China;Applied Entomology Institute, Zhejiang University, Hangzhou 310029, China;Applied Entomology Institute, Zhejiang University, Hangzhou 310029, China;Applied Entomology Institute, Zhejiang University, Hangzhou 310029, China;National Engineering Research Center for Information Technology in Agriculture, Beijing 100089, China
Abstract:From the artificial intelligence point of view, based on the characteristics and feature interpretation of rice pest insects and diseases, a new knowledge expression method based on weight self-adjustment artificial neural networks was presented. In this paper 15 main rice diseases were selected as examples, through classifying, abstracting and coding on the characteristics and feature. The Back Propagation neural network was implemented using neural network and uncertain technology, samples were trained and the weight was regarded as knowledge base to diagnose rice diseases, and in this way rice pest insects and diseases diagnosis expert system was constructed.
Keywords:rice diseases and pest insects  expert system  neural network  weight
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