摘要
将神经网络与传统专家系统有机地结合,建立了用于高炉炉况预测与判断的神经网络专家系统。该系统命中率高、适应性强,且具有良好的自学习功能。
An expert system based on neural networks for predicting and judging the state of blast furnace is developed by applying the method of combining neural networks with traditional expert system. The system with high hit ratio has strong adaptability and good self-learnning function.
出处
《北京科技大学学报》
EI
CAS
CSCD
北大核心
1996年第3期220-225,共6页
Journal of University of Science and Technology Beijing
基金
国家"八五"科技攻关项目
关键词
高炉
炉况
预测
神经网络
专家系统
诊断
blast furnace, predicting the state of BF, neural networks, expert system