decisions(Quality Decisions)depend on scientific analysis of data.Data are collected,generally,in two ways:1)one sample of suitable size,2)subsequent samples,at regular intervals of time.Often the data are considered ...decisions(Quality Decisions)depend on scientific analysis of data.Data are collected,generally,in two ways:1)one sample of suitable size,2)subsequent samples,at regular intervals of time.Often the data are considered normally distributed.This is wrong because the data must be analysed according to their distribution:Decisions are different.In several cases the data are exponentially distributed:we see how to scientifically deal with Control Charts(CC)to decide;this is opposite to what gives the T Charts that are claimed to be a good method for dealing with“rare events”:The Minitab Software(19&20&21)for“T Charts”is considered.The author will compare some methods,found in the literature with the author’s Theory RIT(Reliability Integral Theory):We will see various cases found in the literature.Classical Shewhart Control Charts and the TBE(Time Between Events)Control Charts have been considered:it appears that with RIT the future decisions will be both sounder and cheaper,for data is exponentially distributed.The novelty of the paper is in the scientific way of dealing with the Control Charts and their Control Limits,both with normally distributed data and with exponentially distributed data.In this way,a lot of wrong published papers on“Time Between Events”are to be discarded,even if their authors claim“We used Standard Statistical methods,typical in the vast literature of similar papers”.The author had to self-cite because it seems the only one that has been fighting for years for“Papers Quality”;he humbly asked the readers to inform him if some people did the same.展开更多
随着智慧供热系统建设的不断推进,我国北方地区冬季供热的智能化水平得到重大提升。作为智慧供热系统实现智能化运行的基础,如何实现高效、精准的供热效果评估成为重要的研究课题。该文针对现有评估方法在快速性和准确性方面存在的缺陷...随着智慧供热系统建设的不断推进,我国北方地区冬季供热的智能化水平得到重大提升。作为智慧供热系统实现智能化运行的基础,如何实现高效、精准的供热效果评估成为重要的研究课题。该文针对现有评估方法在快速性和准确性方面存在的缺陷,提出一种基于快速导数动态时间规整(fast derivative dynamic time warping,FDDTW)的供热效果在线评估方法。利用箱线图获取最优参考供温曲线,再将终端用户室温计量装置实时采集到的数据进行滑窗处理,并利用FDDTW计算当前窗口供温曲线和最优参考供温曲线之间的距离,通过FDDTW评估得分判断当前供温效果是否满足实际要求。相较于传统的动态时间规整算法,该算法改善奇异性、提高效率,为智慧供热系统提供切实可行的供热效果在线评估方法。展开更多
文摘decisions(Quality Decisions)depend on scientific analysis of data.Data are collected,generally,in two ways:1)one sample of suitable size,2)subsequent samples,at regular intervals of time.Often the data are considered normally distributed.This is wrong because the data must be analysed according to their distribution:Decisions are different.In several cases the data are exponentially distributed:we see how to scientifically deal with Control Charts(CC)to decide;this is opposite to what gives the T Charts that are claimed to be a good method for dealing with“rare events”:The Minitab Software(19&20&21)for“T Charts”is considered.The author will compare some methods,found in the literature with the author’s Theory RIT(Reliability Integral Theory):We will see various cases found in the literature.Classical Shewhart Control Charts and the TBE(Time Between Events)Control Charts have been considered:it appears that with RIT the future decisions will be both sounder and cheaper,for data is exponentially distributed.The novelty of the paper is in the scientific way of dealing with the Control Charts and their Control Limits,both with normally distributed data and with exponentially distributed data.In this way,a lot of wrong published papers on“Time Between Events”are to be discarded,even if their authors claim“We used Standard Statistical methods,typical in the vast literature of similar papers”.The author had to self-cite because it seems the only one that has been fighting for years for“Papers Quality”;he humbly asked the readers to inform him if some people did the same.
文摘随着智慧供热系统建设的不断推进,我国北方地区冬季供热的智能化水平得到重大提升。作为智慧供热系统实现智能化运行的基础,如何实现高效、精准的供热效果评估成为重要的研究课题。该文针对现有评估方法在快速性和准确性方面存在的缺陷,提出一种基于快速导数动态时间规整(fast derivative dynamic time warping,FDDTW)的供热效果在线评估方法。利用箱线图获取最优参考供温曲线,再将终端用户室温计量装置实时采集到的数据进行滑窗处理,并利用FDDTW计算当前窗口供温曲线和最优参考供温曲线之间的距离,通过FDDTW评估得分判断当前供温效果是否满足实际要求。相较于传统的动态时间规整算法,该算法改善奇异性、提高效率,为智慧供热系统提供切实可行的供热效果在线评估方法。
