Trial mountain climbing algorithm to solve the inverse kinematics problem of redundant manipulator is introduced, and a method of describing a numeral with a special numeration system is given to define the changed st...Trial mountain climbing algorithm to solve the inverse kinematics problem of redundant manipulator is introduced, and a method of describing a numeral with a special numeration system is given to define the changed step of the trail mountain climbing algorithm. The results show that a likelihood solution can be found quickly in the infinite groups of likelihood solutions within the limited search times, and need not calculate the anti trigonometric function and the inverse matrix. In addition, this algorithm has many good qualities such as concise algorithm, tiny computation, fast convergence velocity, good stability and extensive adaptability.展开更多
Sample size re-estimation is essential in oncology studies. However, the use of blinded sample size reassessment for survival data has been rarely reported. Based on the density function of the exponential distributio...Sample size re-estimation is essential in oncology studies. However, the use of blinded sample size reassessment for survival data has been rarely reported. Based on the density function of the exponential distribution, an expectation-maximization（EM） algorithm of the hazard ratio was derived, and several simulation studies were used to verify its applications. The method had obvious variation in the hazard ratio estimates and overestimation for the relatively small hazard ratios. Our studies showed that the stability of the EM estimation results directly correlated with the sample size, the convergence of the EM algorithm was impacted by the initial values, and a balanced design produced the best estimates. No reliable blinded sample size re-estimation inference can be made in our studies, but the results provide useful information to steer the practitioners in this field from repeating the same endeavor.展开更多
In this paper, an Improved Affine-Scaling Interior Point Algorithm for Linear Programming has been proposed. Computational results of selected practical problems affirming the proposed algorithm have been provided. Th...In this paper, an Improved Affine-Scaling Interior Point Algorithm for Linear Programming has been proposed. Computational results of selected practical problems affirming the proposed algorithm have been provided. The proposed algorithm is accurate, faster and therefore reduces the number of iterations required to obtain an optimal solution of a given Linear Programming problem as compared to the already existing Affine-Scaling Interior Point Algorithm. The algorithm can be very useful for development of faster software packages for solving linear programming problems using the interior-point methods.展开更多
文摘Trial mountain climbing algorithm to solve the inverse kinematics problem of redundant manipulator is introduced, and a method of describing a numeral with a special numeration system is given to define the changed step of the trail mountain climbing algorithm. The results show that a likelihood solution can be found quickly in the infinite groups of likelihood solutions within the limited search times, and need not calculate the anti trigonometric function and the inverse matrix. In addition, this algorithm has many good qualities such as concise algorithm, tiny computation, fast convergence velocity, good stability and extensive adaptability.
基金supported by the National Natural Science Foundation of China(81273184)the National Natural Science Foundation of China Grant for Young Scientists (81302512)
文摘Sample size re-estimation is essential in oncology studies. However, the use of blinded sample size reassessment for survival data has been rarely reported. Based on the density function of the exponential distribution, an expectation-maximization（EM） algorithm of the hazard ratio was derived, and several simulation studies were used to verify its applications. The method had obvious variation in the hazard ratio estimates and overestimation for the relatively small hazard ratios. Our studies showed that the stability of the EM estimation results directly correlated with the sample size, the convergence of the EM algorithm was impacted by the initial values, and a balanced design produced the best estimates. No reliable blinded sample size re-estimation inference can be made in our studies, but the results provide useful information to steer the practitioners in this field from repeating the same endeavor.
文摘In this paper, an Improved Affine-Scaling Interior Point Algorithm for Linear Programming has been proposed. Computational results of selected practical problems affirming the proposed algorithm have been provided. The proposed algorithm is accurate, faster and therefore reduces the number of iterations required to obtain an optimal solution of a given Linear Programming problem as compared to the already existing Affine-Scaling Interior Point Algorithm. The algorithm can be very useful for development of faster software packages for solving linear programming problems using the interior-point methods.
