The basic purpose of a quality loss function is to evaluate a loss to customers in a quantitativemanner.Although there are several multivariate loss functions that have been proposed and studied inthe literature,it ha...The basic purpose of a quality loss function is to evaluate a loss to customers in a quantitativemanner.Although there are several multivariate loss functions that have been proposed and studied inthe literature,it has room for improvement.A good multivariate loss function should represent anappropriate compromise in terms of both process economics and the correlation structure amongvarious responses.More important,it should be easily understood and implemented in practice.According to this criterion,we first introduce a pragmatic dimensionless multivariate loss functionproposed by Artiles-Leon,then we improve the multivariate loss function in two respects:one ismaking it suitable for all three types of quality characteristics;the other is considering correlationstructure among the various responses,which makes the improved multivariate loss function moreadequate in the real world.On the bases of these,an example from industrial practice is provided tocompare our improved method with other methods,and last,some reviews are presented inconclusion.展开更多
It is nontrivial to maintain such discovered frequent query patterns in real XML-DBMS because the transaction database of queries may allow frequent updates and such updates may not only invalidate some existing frequ...It is nontrivial to maintain such discovered frequent query patterns in real XML-DBMS because the transaction database of queries may allow frequent updates and such updates may not only invalidate some existing frequent query patterns but also generate some new frequent query patterns. In this paper, two incremental updating algorithms, FUX-QMiner and FUXQMiner, are proposed for efficient maintenance of discovered frequent query patterns and generation the new frequent query patterns when new XMI, queries are added into the database. Experimental results from our implementation show that the proposed algorithms have good performance. Key words XML - frequent query pattern - incremental algorithm - data mining CLC number TP 311 Foudation item: Supported by the Youthful Foundation for Scientific Research of University of Shanghai for Science and TechnologyBiography: PENG Dun-lu (1974-), male, Associate professor, Ph.D, research direction: data mining, Web service and its application, peerto-peer computing.展开更多
This paper investigates systematically the problem of multivariate robustparameter design. First, a measurement criterion for the total variation of multivariate qualitycharacteristics is introduced by the result of i...This paper investigates systematically the problem of multivariate robustparameter design. First, a measurement criterion for the total variation of multivariate qualitycharacteristics is introduced by the result of information theory. Then the implementation procedurein the robust design is presented. After that, a simulation example from a practical industrialprocess is provided. Finally, some comments and further work are discussed.展开更多
文摘The basic purpose of a quality loss function is to evaluate a loss to customers in a quantitativemanner.Although there are several multivariate loss functions that have been proposed and studied inthe literature,it has room for improvement.A good multivariate loss function should represent anappropriate compromise in terms of both process economics and the correlation structure amongvarious responses.More important,it should be easily understood and implemented in practice.According to this criterion,we first introduce a pragmatic dimensionless multivariate loss functionproposed by Artiles-Leon,then we improve the multivariate loss function in two respects:one ismaking it suitable for all three types of quality characteristics;the other is considering correlationstructure among the various responses,which makes the improved multivariate loss function moreadequate in the real world.On the bases of these,an example from industrial practice is provided tocompare our improved method with other methods,and last,some reviews are presented inconclusion.
文摘It is nontrivial to maintain such discovered frequent query patterns in real XML-DBMS because the transaction database of queries may allow frequent updates and such updates may not only invalidate some existing frequent query patterns but also generate some new frequent query patterns. In this paper, two incremental updating algorithms, FUX-QMiner and FUXQMiner, are proposed for efficient maintenance of discovered frequent query patterns and generation the new frequent query patterns when new XMI, queries are added into the database. Experimental results from our implementation show that the proposed algorithms have good performance. Key words XML - frequent query pattern - incremental algorithm - data mining CLC number TP 311 Foudation item: Supported by the Youthful Foundation for Scientific Research of University of Shanghai for Science and TechnologyBiography: PENG Dun-lu (1974-), male, Associate professor, Ph.D, research direction: data mining, Web service and its application, peerto-peer computing.
基金theNationalNaturalScienceFoundationofP.R.ChinaunderGrantNo. 79900018andNo.70372010, andbyAeronauticalScienceFoundationofP. R. ChinaunderGrantNo. 02J55001
文摘This paper investigates systematically the problem of multivariate robustparameter design. First, a measurement criterion for the total variation of multivariate qualitycharacteristics is introduced by the result of information theory. Then the implementation procedurein the robust design is presented. After that, a simulation example from a practical industrialprocess is provided. Finally, some comments and further work are discussed.
