摘要
针对华北某矿井可能出现的2种矿井水,利用其化学数据,构造了自适应线性单元进行突水水源判别。计算结果表明,在训练前进行归一化操作,训练时采用归一化最小均方算法更新权值,可以在相同的训练代数下达到最高的训练精度。
An adaptive linear element （Adaline） is established to discriminate the type of water inrush by using the chemical data of two types of water sources from a certain coal mine in north China. The best training result is obtained by combining the input data normalization and the normalized least mean squares （NLMS） training approach.
作者
彭程
张涛
PENG Cheng1,2, ZHANG Tao1,2(1. Information and Control Technology Institute, North China Institute of Science and Technology, Sanhe 065201, China; 2. Key Laboratory of Safety Monitoring and Control Technology, State Administration of Work Safety, Sanhn 065201, Chin)
出处
《煤炭技术》
CAS
2018年第4期127-128,共2页
Coal Technology
基金
中央高校基本科研业务费资助项目(3142015013)
关键词
突水
水源判别
自适应线性单元
water inrush
discrimination of water sources
Adaline
