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修正时序法在石化装置数据校正中的应用研究
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作者 黄春鹏 夏茂森 《计算机集成制造系统》 EI CSCD 北大核心 2004年第7期858-866,共9页
为了有效地克服传统统计检验和线性化处理方法进行过失误差侦破、数据校正与参数估计时存在的局限性,对现有过程测量数据校正技术进行了综合分析,探讨了数据分类、过失误差侦破和过程测量数据校正等问题,以具有代表性的化工装置和炼油... 为了有效地克服传统统计检验和线性化处理方法进行过失误差侦破、数据校正与参数估计时存在的局限性,对现有过程测量数据校正技术进行了综合分析,探讨了数据分类、过失误差侦破和过程测量数据校正等问题,以具有代表性的化工装置和炼油装置为研究对象,提出了修正时间序列分析法,给出了时间序列分析法的基本思想、概率模型和特点,以及含随机误差的数据校正方法,并将时序法用于过失误差侦破。在大型化工装置的测量数据校正结果表明,该方法是实用性强、方便有效的数据校正新策略。 展开更多
关键词 数据校正 过失误差侦破 修正时序法
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Knowledge mining collaborative DESVM correction method in short-term load forecasting 被引量:3
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作者 牛东晓 王建军 刘金朋 《Journal of Central South University》 SCIE EI CAS 2011年第4期1211-1216,共6页
Short-term forecasting is a difficult problem because of the influence of non-linear factors and irregular events.A novel short-term forecasting method named TIK was proposed,in which ARMA forecasting model was used t... Short-term forecasting is a difficult problem because of the influence of non-linear factors and irregular events.A novel short-term forecasting method named TIK was proposed,in which ARMA forecasting model was used to consider the load time series trend forecasting,intelligence forecasting DESVR model was applied to estimate the non-linear influence,and knowledge mining methods were applied to correct the errors caused by irregular events.In order to prove the effectiveness of the proposed model,an application of the daily maximum load forecasting was evaluated.The experimental results show that the DESVR model improves the mean absolute percentage error(MAPE) from 2.82% to 2.55%,and the knowledge rules can improve the MAPE from 2.55% to 2.30%.Compared with the single ARMA forecasting method and ARMA combined SVR forecasting method,it can be proved that TIK method gains the best performance in short-term load forecasting. 展开更多
关键词 load forecasting support vector regression knowledge mining ARMA differential evolution
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