基于Web的油菜生产专家系统的研究与应用

Research and application of web-based rapeseed (B. napus) production expert system

基于Web的油菜生产专家系统(RPES),在体系结构上,采用了模糊加权产生式规则的知识表示形式和模糊推理机制,以油菜生育时间、浅知识型和深知识型油菜农艺技术措施为尺度建立油菜知识模型,再依此组织知识和知识形式化。PES的主要功能是实现油菜生产产前、产中、产后全程决策服务,模型可视化分析为生产提供辅助决策服务,多媒体知识工具包为用户提供了一个极好的油菜生产知识学习平台。2002年和2003年的实际应用结果表明,由RPES指导的油菜生产地块比对照传统生产地块产量增加10%～19%,净产值增加20%。表4,参12。

In architecture, web-based rapeseed(B. napus) production expert system(RPES) is constituted by a knowledge-base, a database,a model-base,a multimedia information-base, an reasoning engine with weighted fuzzy logic reasoning, system maintenance and user Interface. The knowledge representation(KR) in RPES is weighted fuzzy generated rule. The rapeseed Knowledge Model(KM) is established by the rapeseed growth-development time and agronomic technique measures. And then the knowledge is organized and formatted on the basis of KR and KM. RPES's functions are mainly rapeseed production decision servers in pre-, in-and post-production. Model visual analysis is aided tool for decision, and multimedia knowledge tool package is platform for user to learn rapeseed production knowledge. Field demonstration and application of RPES in 2002 to 2003 showed that the plots conducted by RPES had a yield 10%-19% and net income 20% higher, compared with those in controls.