基于神经网络算法的小蠹科辅助鉴定系统研究  

Research on the assistant identification system of Scolytidae based on the neural network

作　　者：陆军[1] 蒋原[1] 杨光[1] 吴新华[1] 李文欣[2] 张绍红[1] 赵紫华[2] 黄瀚[2] 李志梅[2] 李志红[2] 

机构地区：[1]江苏出入境检验检疫局,江苏南京210001 [2]中国农业大学农学与生物技术学院

出　　处：《植物检疫》2015年第4期21-25,共5页Plant Quarantine

基　　金：科技部质检公益性项目(201310075-2)

摘　　要：小蠹虫是危害森林和木材的一类重要害虫,快速准确鉴定对该类有害生物的防控具有重要意义。本文详细介绍了采用神经网络算法的小蠹科辅助鉴定系统的开发方法、知识获取、知识库构建以及辅助鉴定应用。本系统适合昆虫学专家以及口岸一线植物检疫人员进行小蠹类害虫的鉴定工作。Bark beetle is harmful to the timber and one of the most important pests. How to carry out quick and accurate identification,it has important significance to prevention and control of this kind of pest.The Assistant identification System of Scolytidae was developed in this study which based on the neural network algorithm. This paper introduced the development methods, the knowledge acquirement,the knowledge database establishment and the assistant identification function of this system. This system is more suitable for the assistant identification of Scolytidae to the insect experts and the plant quarantine officers and technicians at ports.

关 键 词：小蠹科 神经网络 鉴定 专家系统 

分 类 号：S126[农业科学—农业基础科学] S41-30