基于径向基函数网络与WebGIS的茶叶病害预测  

Forecast of Disease in Tea Tree Based on Fusion of Radial Basis Function Neural Network and WebGIS

作　　者：叶茂枝[1] 张世良[1] 蔡良绥 

机构地区：[1]宁德师范学院计算机系,福建宁德352100 [2]福建省裕荣香茶业有限公司,福建福鼎355200

出　　处：《三明学院学报》2012年第4期40-44,共5页Journal of Sanming University

基　　金：福建省自然科学基金(2011J01358);宁德师范学院"服务海西建设"项目(2010H313)

摘　　要：利用GIS空间分析与MATLAB数值计算功能的进行模式整合,应用MATLAB神经网络工具箱,从GIS服务器调用参数信息建立RBF神经网络预测模型,将内容反馈给服务器,形成GIS与预测模型的无缝连接,通过We-bGIS对预测模型进行实时动态显示,实现对茶叶病害的预测、查询和诊断。此外,系统具有对空间、属性数据的分析与处理功能,并将抽象的数据转化成清晰简明的电子地图,以直观的图、表显示病害类型及病害地域分布规律,为茶叶病害的诊断防治提供快捷、高效的服务。By using mode integration of GIS spatial analysis and MATLAB numerical functions, the system described in this article applies MATLAB neural network toolbox to call parameters fi＇om the GIS server to establish RBF neural network prediction model, and then send the content back to the server. It makes a seamless connection between GIS and the predictive models and shows in real-time dynamic forecasting model by the WebGIS, which achieve the forecast tea disease for querying, forecasting and diagnostics. In addition, the system has a processing and analysis function in spatial and attribute data and transform abstract data into clear and concise electronic maps in graph or table format to show tea disease type and the rule of geographic distribution. It makes efficient service for the disease diagnosis and prevention conveniently.

关 键 词：茶叶 病害 预测 径向基函数网络 WEBGIS 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]