CAJ | 학술논문

为了掌握钢铁企业自备电厂煤气供入量的变化趋势，基于采样数据建立了自回归移动平均（ARMA）模型，利用拉格朗日乘数法（LM）检验出 ARMA 模型残差存在自回归条件异方差（ARCH）效应，建立ARMA-ARCH模型．分别使用ARMA模型和ARMA-ARCH模型进行短期预测，并比较两者的精度．最后基于概率分布对扰动项进行统计分析，得到生产中稳定性差是导致扰动项大的主要原因，与实际生产相吻合．研究表明，ARMA-ARCH模型的预测精度较高，预测误差为4.11％，能够较为准确地预测出钢铁企业自备电厂煤气供入量变化趋势，对实际生产中频繁调节锅炉开关和优化调度决策有着重要的作用．
위료장악강철기업자비전엄매기공입량적변화추세，기우채양수거건립료자회귀이동평균（ARMA）모형，이용랍격랑일승수법（LM）검험출 ARMA 모형잔차존재자회귀조건이방차（ARCH）효응，건립ARMA-ARCH모형．분별사용ARMA모형화ARMA-ARCH모형진행단기예측，병비교량자적정도．최후기우개솔분포대우동항진행통계분석，득도생산중은정성차시도치우동항대적주요원인，여실제생산상문합．연구표명，ARMA-ARCH모형적예측정도교고，예측오차위4.11％，능구교위준학지예측출강철기업자비전엄매기공입량변화추세，대실제생산중빈번조절과로개관화우화조도결책유착중요적작용．
Varying tendency forecasting is very important to the residual gas supply of self-provided power plant in iron and steel industry.By applying the Eviews software,ARMA (Auto-Regressive Moving Average)model of varying tendency for residual gas supply is built.Through ARCH (Auto-Regressive Conditional Heteroskedastic) effect tests of the residual of ARMA model by Lagrange multiplier,the corresponding ARMA-ARCH model is also set up.The varying tendency series are forecasted by using ARMA model and ARMA-ARCH model respectively. Forecasting precision of ARMA model and ARMA -ARCH model is then compared.In this model,probability distribution is used to analyze the residual series in combination with the real production.The results indicate that the proposed model has a well -pleasing forecast performance with a Mean Abs.Percent Error (MAPE )of 4. 1 1%.The case study shows that the model performs well to forecast the varying tendency,which can be used to keep production balance and ensure the pipeline network pressure in a safe range.