Neural network can solve some problems of blast furnace expert system such as knowledge getting and inference ability, and it is suitable for pattern recognition of blast furnace data distribution.
神经网络可以解决高炉专家系统最困难的知识获取与推理能力弱等问题，并适合于对高炉分布数据进行模式识别。
On the basis of blast furnace sensor data, BFDES system can make real-time judgement of furnace condition and predict the failure of the blast furnace.
根据高炉传感器的数据，BFDES系统可对高炉炉况作出实时判断，并可预测高炉运行的故障。
The numerical simulation model and prediction model on the blast furnace form an integrated analysis system, which is applied to actual production blast furnace and proved to be of practical value.
高炉过程的数值解析及软融带推断形成了比较完整的炉内状况分析体系，在实际高炉生产中的应用表明，该体系具有很好的实用价值。
应用推荐