摘要
采集 8 0组黄埔电厂入厂煤煤质分析数据 ,应用人工神经网络方法建立了非线性模型 ,研究煤质特性指标间的关系 ,通过非线性模型计算煤炭的发热量 ,得到了令人满意的结果。一方面 ,说明煤质特性指标间关系的复杂性 ;另一方面 ,表明人工神经网络方法处理非线性问题的有效性。图 3表 3参
To study the relationship among characteristic indexes of raw coal, 80 groups of analystical data of raw coal in Huangpu Power Plant were processing based on nonlinear matrix with the artificial neural network method. The predicted calorific value of 95% raw coal is below the allowable deviation (300J/g) of the national standards. It is indicated that the relationship among the indexes is complicated, and the artificial neural network method could represent the nonlinear relationship in effect. Figs.3, tables 3 and refs 8.
出处
《动力工程》
CSCD
北大核心
2003年第4期2603-2607,共5页
Power Engineering
关键词
煤
非线性模型
煤质特性指标
人工神经网络
coal
nonlinear matrix
characteristic indexes of coal quality
artificial neural network