Computer simulation models may by used to gain further information about missile performance variability. Model validation is an important aspect of the test program for a missile system. Validation provides a basis f...Computer simulation models may by used to gain further information about missile performance variability. Model validation is an important aspect of the test program for a missile system. Validation provides a basis for confidence in the model's results and is a necessary step if the model is to be used to draw inference about the behavior of the real missile. This paper is a review of methods useful for validation of computer simulation models of missile systems and provides a new method with high degree of confidence for validation of computer simulation models of missile systems. Some examples of the use of the new method in validating computer simulation models are given.展开更多
Distribution-based degradation models （or graphical approach in some literature） occur in a wide range of applications. However, few of existing methods have taken the validation of the built model into consideratio...Distribution-based degradation models （or graphical approach in some literature） occur in a wide range of applications. However, few of existing methods have taken the validation of the built model into consideration. A validation methodology for distribution-based models is proposed in this paper. Since the model can be expressed as consisting of assumptions of model structures and embedded model parameters, the proposed methodology carries out the validation from these two aspects. By using appropriate statistical techniques, the rationality of degradation distributions, suitability of fitted models and validity of degradation models are validated respectively. A new statistical technique based on control limits is also proposed, which can be implemented in the validation of degradation models＇ validity. The case study on degradation modeling of an actual accelerometer shows that the proposed methodology is an effective solution to the validation problem of distribution-based de qradation models.展开更多
The quantitative structure-property relationship(QSPR) of anabolic androgenic steroids was studied on the half-wave reduction potential(E1/2) using quantum and physico-chemical molecular descriptors. The descriptors w...The quantitative structure-property relationship(QSPR) of anabolic androgenic steroids was studied on the half-wave reduction potential(E1/2) using quantum and physico-chemical molecular descriptors. The descriptors were calculated by semi-empirical calculations. Models were established using partial least square(PLS) regression and back-propagation artificial neural network(BP-ANN). The QSPR results indicate that the descriptors of these derivatives have significant relationship with half-wave reduction potential. The stability and prediction ability of these models were validated using leave-one-out cross-validation and external test set.展开更多
The thermal decomposition temperature is one of the most important parameters to evaluate fire hazard of organic peroxide. A quantitative structure-property relationship model was proposed for estimating the thermal d...The thermal decomposition temperature is one of the most important parameters to evaluate fire hazard of organic peroxide. A quantitative structure-property relationship model was proposed for estimating the thermal decomposition temperatures of organic peroxides. The entire set of 38 organic peroxides was at random divided into a training set for model development and a prediction set for external model validation. The novel local molecular descriptors of AT1, AT2, AT3, AT4, AT5, AT6 and global molecular descriptor of ATC have been proposed in order to character organic peroxides’ molecular structures. An accurate quantitative structure-property relationship （QSPR） equation is developed for the thermal decomposition temperatures of organic peroxides. The statistical results showed that the QSPR model was obtained using the multiple linear regression （MLR） method with correlation coefficient （R）, standard deviation （S）, leave-one-out validation correlation coefficient （RCV） values of 0.9795, 6.5676 ℃ and 0.9328, respectively. The average absolute relative deviation （AARD） is only 3.86% for the experimental values. Model test by internal leave-one-out cross validation and external validation and molecular descriptor interpretation were discussed. Comparison with literature results demonstrated that novel local and global descriptors were useful molecular descriptors for predicting the thermal decomposition temperatures of organic peroxides.展开更多
文摘Computer simulation models may by used to gain further information about missile performance variability. Model validation is an important aspect of the test program for a missile system. Validation provides a basis for confidence in the model's results and is a necessary step if the model is to be used to draw inference about the behavior of the real missile. This paper is a review of methods useful for validation of computer simulation models of missile systems and provides a new method with high degree of confidence for validation of computer simulation models of missile systems. Some examples of the use of the new method in validating computer simulation models are given.
文摘Distribution-based degradation models （or graphical approach in some literature） occur in a wide range of applications. However, few of existing methods have taken the validation of the built model into consideration. A validation methodology for distribution-based models is proposed in this paper. Since the model can be expressed as consisting of assumptions of model structures and embedded model parameters, the proposed methodology carries out the validation from these two aspects. By using appropriate statistical techniques, the rationality of degradation distributions, suitability of fitted models and validity of degradation models are validated respectively. A new statistical technique based on control limits is also proposed, which can be implemented in the validation of degradation models＇ validity. The case study on degradation modeling of an actual accelerometer shows that the proposed methodology is an effective solution to the validation problem of distribution-based de qradation models.
基金Project supported by the Postdoctoral Science Foundation of Central South University,ChinaProject(2015SK20823)supported by Science and Technology Project of Hunan Province,China+2 种基金Project(15A001)supported by Scientific Research Fund of Hunan Provincial Education Department,ChinaProject(CX2015B372)supported by Hunan Provincial Innovation Foundation for Postgraduate,ChinaProject supported by Innovation Experiment Program for University Students of Changsha University of Science and Technology,China
文摘The quantitative structure-property relationship(QSPR) of anabolic androgenic steroids was studied on the half-wave reduction potential(E1/2) using quantum and physico-chemical molecular descriptors. The descriptors were calculated by semi-empirical calculations. Models were established using partial least square(PLS) regression and back-propagation artificial neural network(BP-ANN). The QSPR results indicate that the descriptors of these derivatives have significant relationship with half-wave reduction potential. The stability and prediction ability of these models were validated using leave-one-out cross-validation and external test set.
基金Project(2015SK20823) supported by Science and Technology Project of Hunan Province,ChinaProject(15A001) supported by Scientific Research Fund of Hunan Provincial Education Department,China+2 种基金Project(2017CL06) supported by Hunan Provincial Key Laboratory of Materials Protection for Electric Power and Transportation,ChinaProject(k1403029-11) supported by Science and Technology Project of Changsha City,ChinaProject(CX2015B372) supported by the Hunan Provincial Innovation Foundation for Postgraduate,China
文摘The thermal decomposition temperature is one of the most important parameters to evaluate fire hazard of organic peroxide. A quantitative structure-property relationship model was proposed for estimating the thermal decomposition temperatures of organic peroxides. The entire set of 38 organic peroxides was at random divided into a training set for model development and a prediction set for external model validation. The novel local molecular descriptors of AT1, AT2, AT3, AT4, AT5, AT6 and global molecular descriptor of ATC have been proposed in order to character organic peroxides’ molecular structures. An accurate quantitative structure-property relationship （QSPR） equation is developed for the thermal decomposition temperatures of organic peroxides. The statistical results showed that the QSPR model was obtained using the multiple linear regression （MLR） method with correlation coefficient （R）, standard deviation （S）, leave-one-out validation correlation coefficient （RCV） values of 0.9795, 6.5676 ℃ and 0.9328, respectively. The average absolute relative deviation （AARD） is only 3.86% for the experimental values. Model test by internal leave-one-out cross validation and external validation and molecular descriptor interpretation were discussed. Comparison with literature results demonstrated that novel local and global descriptors were useful molecular descriptors for predicting the thermal decomposition temperatures of organic peroxides.
