摘要
借助先进的近红外光谱仪器,以国家标准为指导,得到一系列煤样光谱及其各项指标的标准值。分别建立基于BP神经网络和偏最小二乘法的煤质近红外光谱定量分析模型,并利用VC和SQL语言设计开发分析软件。结果表明:煤质近红外光谱分析系统可准确地对煤炭指标进行分析预测。
With the aid of advanced near infrared spectrum instrument, guided by the national standard, get a series of coal sample spectrum. Respectively based on BP neural networks and partial least squares of the near infrared spectrum of coal analysis model, and use the VC and SQL language design, analysis and develop software. the results show that the coal near infrared spectrum analysis system can accurately predict coal index analysis.
出处
《煤炭技术》
CAS
北大核心
2016年第2期297-299,共3页
Coal Technology
基金
国家自然科学基金项目(61303183)
中国博士后科学基金(2014M551695)
青年基金项目(Bk20140215)
关键词
煤质
近红外光谱分析
BP神经网络
偏最小二乘
coal quality
near infrared spectroscopy
BP neural network
partial least squares
