摘要
在对程潮铁矿采准巷道支护类型影响因素和巷道成功加固实例调查分析的基础上,提出采用改进的BP神经网络对支护类型进行研究。由学习样本的学习过程和对支护类型的预测结果可知,无论是学习样本误差收敛过程,还是收敛速度、收敛精度和支护类型的预测结果都较为理想,预测准确率较高,为研究采准巷道的支护类型提供了新的研究思路,具有较好的推广应用价值。
Based on the investigation and analyse of the factors affecting the support type of development roadways as well as the successful support cases in Chengchao Iron Mine, it was proposed to use an improved BP neutral network in the study of support type. It can be seen from the learning course of learning samples and the predition results of support types that ideal results of prediction with high accuracy were achieved for both the error astringent process, speed and accuracy and the support types of learning samples, providing a new thought on the research of support types of development roadways. Thus, it is of good popularization value.
出处
《金属矿山》
CAS
北大核心
2005年第3期19-21,37,共4页
Metal Mine
