摘要
利用人工智能技术对全断面岩石掘进机进行优化选型,实现掘进机方案设计智能化。针对隧道掘进机选型领域知识的特点,在知识获取中分别应用两种不同的机器学习方法:实例学习和类推学习,形成了一种协同推理模型;采用Microsoft公司的可视化集成开发工具Visual Foxpro 6.0在Windows平台上建立了知识库,开发了基于人工神经网络和范例推理系统的功能模块,建造了掘进机智能选型方案生成系统原型;通过案例对该系统进行了验证。将该系统应用在掘进机选型智能决策系统中,可以有效地指导掘进机的设计与选用。
Using artificial intelligence to make a type selection of full face rock tunnel boring machine an intelligent design system was established. For acquiring knowledge, according to the features of type selection two different machine learning methods were applied by cases and by reasoning, and a cooperative reasoning model was established. A knowledge-based system was built using Visual Foxpro 6.0, and a functional module based on artificial neural network and case--based reasoning was formed, the prototype of intelligent type selection was developed, then some cases were used to testify the system. Applying the system in tunnel boring machine intelligent type selection,it can direct the design and selection of tunnel boring machine effectively.
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2007年第6期681-686,共6页
China Mechanical Engineering
基金
"十五"国家重大技术装备研制项目(ZZ02-03-03-01)
关键词
智能设计
隧道掘进机
选型
人工神经网络
范例推理
intelligent design
tunnel boring machine
type selection
artificial neural network
case -- based reasoning
