accurate calculation of reliability index is very important for the reliability analysis of structures. in some limit state functions with nonlinear characteristic and several local optimum design points, the computational reliability methods may not appropriately determine the failure probability, and iterative reliability approaches may be converged to local optimum design points. in this pap...

Nonlinear conjugate gradient (CG) methods are very important for solving unconstrained optimization problems. These have been subjected to extensive researches in terms of enhancing them. Exact and strong Wolfe line search techniques usually used practice the analysis implementation methods. For better results, several studies carried out modify classical CG The method Fletcher Reeves (FR) is o...

The conjugate gradient approach is a powerful tool that used in variety of areas to solve problems involving large-scale reduction. In this paper, we propose new parameter nonlinear algorithms fuzzy equations based on Polak and Ribiere (PRP) method, where prove the descent global convergence properties proposed algorithm. terms numerical results, method has been compared with methods Fletcher (...

<p>The conjugate gradient methods are noted to be exceedingly valuable for solving large-scale unconstrained optimization problems since it needn't the storage of matrices. Mostly parameter is focus methods. The current paper proposes new type solve optimization. A Hessian approximation in a diagonal matrix form on basis second and third-order Taylor series expansion was employed this stu...

In ultrasound inverse problems, the integral equation can be nonlinear, ill-posed, and computationally expensive. One approach to solving such problems is the conjugate gradient (CG) method. A key parameter in the CG method is the conjugate gradient direction. In this paper, we investigate the CG directions proposed by Polyak et al. (PPR), Hestenes and Stiefel (HS), Fletcher and Reeves (FR), Da...