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 …

Conjugate Gradient (CG) method is the most prominent iterative mathematical technique
that can be useful for the optimization of both linear and non-linear systems due to its …

The area of unconstrained optimization has been enjoying vivid growth recently, with
significant progress on numerical innovative techniques. The classical technique for …

The three-term conjugate gradient (CG) algorithms are among the efficient variants of CG
method for convex and nonconvex functions. This is because most three-term algorithms are …

Step sizes is very important for a global convergence gradient method for solving the
problems of unconstrained optimization. The new step sizes formulas techniques proposed …

To solve large-scale nonlinear equations with convex constraints efficiently and overcome
the shortcomings of other algorithms, such as large storage and high complexity, we …

The WYL-type conjugate gradient (CG) iterative formulas have been widely studied by
researchers because of their effective and robust algorithms as well as less memory …

One of the most significant problems in fuzzy set theory is solving fuzzy nonlinear equations.
Numerous researches have been done on numerical methods for solving these problems …

The conjugate gradient (CG) algorithms are one of the efficient numerical algorithms that are
characterized by simplicity and nice convergence properties. However, recent modification …

Least squares models appear frequently in many fields, such as data fitting, signal
processing, machine learning, and especially artificial intelligence. Nowadays, the model is …