This paper considers experimental situations where the interested effects have to be or- thogonal to a set of nonnegligible effects. It is shown that various types of orthogonal arrays with mixed strength are A-optima...This paper considers experimental situations where the interested effects have to be or- thogonal to a set of nonnegligible effects. It is shown that various types of orthogonal arrays with mixed strength are A-optimal for estimating the parameters in ANOVA high dimension model representation. Both cases including interactions or not are considered in the model. In particularly, the estimations of all main effects are A-optimal in a mixed strength （2, 2）3 orthogonal array and the estimations of all main effects and two-factor interactions in G~ x G~ are A-optimal in a mixed strength （2, 2）4 orthogonal array. The properties are also illustrated through a simulation study.展开更多
Considering the complex nonlinear relationship between the material parameters of a concrete faced rock-fill dam(CFRD) and its displacements, the harmony search(HS) algorithm is used to optimize the back propagation n...Considering the complex nonlinear relationship between the material parameters of a concrete faced rock-fill dam(CFRD) and its displacements, the harmony search(HS) algorithm is used to optimize the back propagation neural network(BPNN), and the HS-BPNN algorithm is formed and applied for the inversion analysis of the parameters of rock-fill materials. The sensitivity of the parameters in the Duncan and Chang's E-B model is analyzed using the orthogonal test design. The case study shows that the parameters φ0, K, Rf, and Kb are sensitive to the deformation of the rock-fill dam and the inversion analysis for these parameters is performed by the HS-BPNN algorithm. Compared with the traditional BPNN, the HS-BPNN algorithm exhibits the advantages of high convergence precision, fast convergence rate, and strong stability.展开更多
基金the National Natural Science Foundation of China under Grant Nos.11171065,11301073the Natural Science Foundation of Jiangsu under Grant No.BK20141326+1 种基金the Research Fund for the Doctoral Program of Higher Education of China under Grant No.20120092110021Scientific Research Foundation of Graduate School of Southeast University under Grant No.YBJJ1444
文摘This paper considers experimental situations where the interested effects have to be or- thogonal to a set of nonnegligible effects. It is shown that various types of orthogonal arrays with mixed strength are A-optimal for estimating the parameters in ANOVA high dimension model representation. Both cases including interactions or not are considered in the model. In particularly, the estimations of all main effects are A-optimal in a mixed strength （2, 2）3 orthogonal array and the estimations of all main effects and two-factor interactions in G~ x G~ are A-optimal in a mixed strength （2, 2）4 orthogonal array. The properties are also illustrated through a simulation study.
基金supported by the National Natural Science Foundation of China(Grant Nos.51579086,51479054,51379068&51139001)Jiangsu Natural Science Foundation(Grant No.BK20140039)the Priority Academic Program Development of Jiangsu Higher Education Institutions(Grant No.YS11001)
文摘Considering the complex nonlinear relationship between the material parameters of a concrete faced rock-fill dam(CFRD) and its displacements, the harmony search(HS) algorithm is used to optimize the back propagation neural network(BPNN), and the HS-BPNN algorithm is formed and applied for the inversion analysis of the parameters of rock-fill materials. The sensitivity of the parameters in the Duncan and Chang's E-B model is analyzed using the orthogonal test design. The case study shows that the parameters φ0, K, Rf, and Kb are sensitive to the deformation of the rock-fill dam and the inversion analysis for these parameters is performed by the HS-BPNN algorithm. Compared with the traditional BPNN, the HS-BPNN algorithm exhibits the advantages of high convergence precision, fast convergence rate, and strong stability.
