节点文献
煤炭地下气化过程灰色预测
Gray Prediction of Underground Coal Gasification Process
【摘要】 煤炭地下气化系统是一个信息部分明确、部分不明确的灰色系统,针对这一问题,建立了煤炭地下气化过程状态参数灰色数列预测模型和系统预测模型;实际应用结果表明,数列预测的误差是在8.92%~14.47%之间,系统预测的误差在0.13%~16.6%之间,而采用等维新息模型,形成等维灰数递补动态预测,可减少预测误差.“灰色预测”模型能够指导操作人员作出定性或定量分析,从而事先调控煤炭地下气化生产过程,实现连续稳定生产.
【Abstract】 Underground coal gasification(UCG) is a gray system with part of clear information, the gray sequence prediction model and systematical prediction model for state parameters of UCG process were developed. The results show that the error of sequence prediction lies in 8. 92%-14. 47% while that of systemic prediction lies in 0. 13%-14. 47%. However, the error can be decreased by using dynamic prediction of equal-dimensional gray data based on equal-dimensional information model. Therefore gray prediction is helpful for the operators to make qualitative and quantitative analysis, which will be beneficial to UCG control and production.
【Key words】 underground coal gasification; state parameter; sequence prediction; systematical prediction;
- 【文献出处】 中国矿业大学学报 ,Journal of China University of Mining & Technology , 编辑部邮箱 ,2003年06期
- 【分类号】TD84
- 【被引频次】6
- 【下载频次】181