In this work,we construct and study a family of robust nonparametric estimators for a regression function based on kernel methods.The data are functional,independent and identically distributed,and are linked to a sin...In this work,we construct and study a family of robust nonparametric estimators for a regression function based on kernel methods.The data are functional,independent and identically distributed,and are linked to a single-index model.Under general conditions,we establish the pointwise and uniform almost complete convergence,as well as the asymptotic normality of the estimator.We explicitly derive the asymptotic variance and,as a result,provide confidence bands for the theoretical parameter.A simulation study is conducted to illustrate the proposed methodology.展开更多
Landslides are common natural hazards occurring in most parts of the world and have considerable adverse economic effects. Residual shear strength of clay is one of the most important factors in the determination of s...Landslides are common natural hazards occurring in most parts of the world and have considerable adverse economic effects. Residual shear strength of clay is one of the most important factors in the determination of stability of slopes or landslides. This effect is more pronounced in sensitive clays which show large changes in shear strength from peak to residual states. This study analyses the prediction of the residual strength of clay based on a new prediction model, functional networks（FN） using data available in the literature. The performance of FN was compared with support vector machine（SVM） and artificial neural network（ANN） based on statistical parameters like correlation coefficient（R）, Nash–Sutcliff coefficient of efficiency（E）, absolute average error（AAE）, maximum average error（MAE） and root mean square error（RMSE）. Based on R and E parameters, FN is found to be a better prediction tool than ANN for the given data. However, the R and E values for FN are less than SVM. A prediction equation is presented that can be used by practicing geotechnical engineers. A sensitivity analysis is carried out to ascertain the importance of various inputs in the prediction of the output.展开更多
Extenics was a branch of mathematics for studying the incompatible problems. In this paper, basing on calculating the associative functions of all various indexes, we have obtained the quantitative assessment results ...Extenics was a branch of mathematics for studying the incompatible problems. In this paper, basing on calculating the associative functions of all various indexes, we have obtained the quantitative assessment results of prediction indexes by introducing this theory into the comprehensive earthquake prediction through establishing the matter-element model for comprehensive prediction, so that the incompatible problems can be solved. The preliminary results demonstrate that this method has better prospects in comprehensive earthquake prediction.展开更多
By establishing the VEC model, the relationship between Consumer Price Index (CPI) and Producer Price Index (PPI) is explored by using Johansen cointegration test and impulse response function. The results show that t...By establishing the VEC model, the relationship between Consumer Price Index (CPI) and Producer Price Index (PPI) is explored by using Johansen cointegration test and impulse response function. The results show that there is a long-term equilibrium cointegration relationship between CPI and PPI. CPI has a certain impact on PPI. PPI also has a certain impact on CPI. PPI has a great impact on itself both in the long-term and short-term. The current CPI will be adversely affected by the previous CPI and the positive impact of the previous PPI. The current PPI will be positively affected by the previous phase of CPI and the previous phase of PPI.展开更多
基金supported by PRFU of Ministry of Higher Education and Scientific Research Algeria(MESRS),University of Sciences and Technology Oran Mohamed Boudiaf(USTO-MB),Code:C00L03UN310220230005.
文摘In this work,we construct and study a family of robust nonparametric estimators for a regression function based on kernel methods.The data are functional,independent and identically distributed,and are linked to a single-index model.Under general conditions,we establish the pointwise and uniform almost complete convergence,as well as the asymptotic normality of the estimator.We explicitly derive the asymptotic variance and,as a result,provide confidence bands for the theoretical parameter.A simulation study is conducted to illustrate the proposed methodology.
文摘Landslides are common natural hazards occurring in most parts of the world and have considerable adverse economic effects. Residual shear strength of clay is one of the most important factors in the determination of stability of slopes or landslides. This effect is more pronounced in sensitive clays which show large changes in shear strength from peak to residual states. This study analyses the prediction of the residual strength of clay based on a new prediction model, functional networks（FN） using data available in the literature. The performance of FN was compared with support vector machine（SVM） and artificial neural network（ANN） based on statistical parameters like correlation coefficient（R）, Nash–Sutcliff coefficient of efficiency（E）, absolute average error（AAE）, maximum average error（MAE） and root mean square error（RMSE）. Based on R and E parameters, FN is found to be a better prediction tool than ANN for the given data. However, the R and E values for FN are less than SVM. A prediction equation is presented that can be used by practicing geotechnical engineers. A sensitivity analysis is carried out to ascertain the importance of various inputs in the prediction of the output.
文摘Extenics was a branch of mathematics for studying the incompatible problems. In this paper, basing on calculating the associative functions of all various indexes, we have obtained the quantitative assessment results of prediction indexes by introducing this theory into the comprehensive earthquake prediction through establishing the matter-element model for comprehensive prediction, so that the incompatible problems can be solved. The preliminary results demonstrate that this method has better prospects in comprehensive earthquake prediction.
文摘By establishing the VEC model, the relationship between Consumer Price Index (CPI) and Producer Price Index (PPI) is explored by using Johansen cointegration test and impulse response function. The results show that there is a long-term equilibrium cointegration relationship between CPI and PPI. CPI has a certain impact on PPI. PPI also has a certain impact on CPI. PPI has a great impact on itself both in the long-term and short-term. The current CPI will be adversely affected by the previous CPI and the positive impact of the previous PPI. The current PPI will be positively affected by the previous phase of CPI and the previous phase of PPI.
