An MPPT (Maximum Power Point Tracking) plays a vital role in photovoltaic(PV) power generation system. Applying the optimum is significant way to achieve an efficient PV The methods’ efficiency counts on two factors, including perturbation period and amplitude. Nevertheless, realizing photovoltaic array very hard when natural conditions change, especially for temperature light intensity. This p...

This work proposes proposed a technique inspired by memetic algorithm (MA) to improve the convergence of iterative methods for solving systems of equations. In the first phase the system of equations is transformed into an optimization problem. In this first phase, a memetics technique -ie a double optimization, local and globalis used to determine an initial vector favorable to a rapid converg...

It is shown that the four vector extrapolation methods, minimal polynomial extrapolation, reduced rank extrapolation, modified minimal polynomial extrapolation, and topological epsilon algorithm, when applied to linearly generated vector sequences, are Krylov subspace methods, and are equivalent to some well known conjugate gradient type methods. A unified recursive method that includes the con...

The conjugate gradient optimization algorithm usually used for nonlinear least squares is presented and is combined with the modified back propagation algorithm yielding a new fast training multilayer perceptron (MLP) algorithm (CGFR/AG). The approaches presented in the paper consist of three steps: (1) Modification on standard back propagation algorithm by introducing gain variation term of th...

A new framework based on the curved Riemannian manifold is proposed to calculate the numerical solution of the Lyapunov matrix equation by using a natural gradient descent algorithm and taking the geodesic distance as the objective function. Moreover, a gradient descent algorithm based on the classical Euclidean distance is provided to compare with this natural gradient descent algorithm. Furth...

We compare the performance of several robust large-scale minimization algorithms for the unconstrained minimization of an ill-posed inverse problem. The parabolized Navier–Stokes equation model was used for adjoint parameter estimation. The methods compared consist of three versions of nonlinear conjugate-gradient (CG) method, quasiNewton Broyden–Fletcher–Goldfarb–Shanno (BFGS), the limited-mem...

In this paper, we seek the conjugate gradient direction closest to the direction of the scaled memoryless BFGS method and propose a family of conjugate gradient methods for unconstrained optimization. An improved Wolfe line search is also proposed, which can avoid a numerical drawback of the Wolfe line search and guarantee the global convergence of the conjugate gradient method under mild condi...