Open Ground Storey（OGS） framed buildings where the ground storey is kept open without infill walls, mainly to facilitate parking, is increasing commonly in urban areas. However, vulnerability of this type of buildin...Open Ground Storey（OGS） framed buildings where the ground storey is kept open without infill walls, mainly to facilitate parking, is increasing commonly in urban areas. However, vulnerability of this type of buildings has been exposed in past earthquakes. OGS buildings are conventionally designed by a bare frame analysis that ignores the stiffness of the infill walls present in the upper storeys, but doing so underestimates the inter-storey drift（ISD） and thereby the force demand in the ground storey columns. Therefore, a multiplication factor（MF） is introduced in various international codes to estimate the design forces（bending moments and shear forces） in the ground storey columns. This study focuses on the seismic performance of typical OGS buildings designed by means of MFs. The probabilistic seismic demand models, fragility curves, reliability and cost indices for various frame models including bare frames and fully infilled frames are developed. It is found that the MF scheme suggested by the Israel code is better than other international codes in terms of reliability and cost.展开更多
The concept of upper variance under multiple probabilities is defined through a corresponding minimax optimization problem.This study proposes a simple algorithm to solve this optimization problem exactly.Additionally...The concept of upper variance under multiple probabilities is defined through a corresponding minimax optimization problem.This study proposes a simple algorithm to solve this optimization problem exactly.Additionally,we provide a probabilistic representation for a class of quadratic programming problems,demonstrating the practical application of our approach.展开更多
The probability of default(PD) is the key element in the New Basel Capital Accord and the most essential factor to financial institutions' risk management.To obtain good PD estimation,practitioners and academics h...The probability of default(PD) is the key element in the New Basel Capital Accord and the most essential factor to financial institutions' risk management.To obtain good PD estimation,practitioners and academics have put forward numerous default prediction models.However,how to use multiple models to enhance overall performance on default prediction remains untouched.In this paper,a parametric and non-parametric combination model is proposed.Firstly,binary logistic regression model(BLRM),support vector machine(SVM),and decision tree(DT) are used respectively to establish models with relatively stable and high performance.Secondly,in order to make further improvement to the overall performance,a combination model using the method of multiple discriminant analysis(MDA) is constructed.In this way,the coverage rate of the combination model is greatly improved,and the risk of miscarriage is effectively reduced.Lastly,the results of the combination model are analyzed by using the K-means clustering,and the clustering distribution is consistent with a normal distribution.The results show that the combination model based on parametric and non-parametric can effectively enhance the overall performance on default prediction.展开更多
文摘Open Ground Storey（OGS） framed buildings where the ground storey is kept open without infill walls, mainly to facilitate parking, is increasing commonly in urban areas. However, vulnerability of this type of buildings has been exposed in past earthquakes. OGS buildings are conventionally designed by a bare frame analysis that ignores the stiffness of the infill walls present in the upper storeys, but doing so underestimates the inter-storey drift（ISD） and thereby the force demand in the ground storey columns. Therefore, a multiplication factor（MF） is introduced in various international codes to estimate the design forces（bending moments and shear forces） in the ground storey columns. This study focuses on the seismic performance of typical OGS buildings designed by means of MFs. The probabilistic seismic demand models, fragility curves, reliability and cost indices for various frame models including bare frames and fully infilled frames are developed. It is found that the MF scheme suggested by the Israel code is better than other international codes in terms of reliability and cost.
文摘The concept of upper variance under multiple probabilities is defined through a corresponding minimax optimization problem.This study proposes a simple algorithm to solve this optimization problem exactly.Additionally,we provide a probabilistic representation for a class of quadratic programming problems,demonstrating the practical application of our approach.
基金supported by the National Natural Science Foundation of China Key Project under Grant No.70933003the National Natural Science Foundation of China under Grant Nos.70871109 and 71203247
文摘The probability of default(PD) is the key element in the New Basel Capital Accord and the most essential factor to financial institutions' risk management.To obtain good PD estimation,practitioners and academics have put forward numerous default prediction models.However,how to use multiple models to enhance overall performance on default prediction remains untouched.In this paper,a parametric and non-parametric combination model is proposed.Firstly,binary logistic regression model(BLRM),support vector machine(SVM),and decision tree(DT) are used respectively to establish models with relatively stable and high performance.Secondly,in order to make further improvement to the overall performance,a combination model using the method of multiple discriminant analysis(MDA) is constructed.In this way,the coverage rate of the combination model is greatly improved,and the risk of miscarriage is effectively reduced.Lastly,the results of the combination model are analyzed by using the K-means clustering,and the clustering distribution is consistent with a normal distribution.The results show that the combination model based on parametric and non-parametric can effectively enhance the overall performance on default prediction.
