Conjugate gradient method is a numerical method that can find the minima of the function in the hyper-dimensional space, and conjugate gradient method includes linear conjugate method and non-linear ...

The nonlinear conjugate gradient method is a very useful technique for solving large scale minimization problems and has wide applications in many fields. In this paper, we present a new algorithm of ...

NCG-Optimizer is a set of optimizer about nonlinear conjugate gradient in PyTorch. Inspired by @jettify and @kozistr. The Linear Conjugate Gradient(LCG) method is only applicable to linear equation ...

Abstract: For the conjugate gradient method to solve the unconstrained optimization problem, given a new interval method to obtain the direction parameters, and a new conjugate gradient algorithm is ...

Conjugate gradient methods form a class of iterative algorithms that are highly effective for solving large‐scale unconstrained optimisation problems. They achieve efficiency by constructing search ...

This paper proposes a bridge moving load identification method based on the Fractional Conjugate Gradient (FCG) method to address the low identification accuracy of traditional conjugate gradient ...

Abstract: This paper extends the conjugate gradient minimization method of Fletcher and Reeves to optimal control problems. The technique is directly applicable only to unconstrained problems; if ...

ABSTRACT: In this paper, an efficient computational algorithm is proposed to solve the nonlinear optimal control problem. In our approach, the linear quadratic optimal control model, which is adding ...

ABSTRACT: In conjugate gradient method, it is well known that the recursively computed residual differs from true one as the iteration proceeds in finite arithmetic. Some work have been devoted to ...