Modified spectral conjugate gradient iterative scheme for unconstrained optimization problems with application on COVID-19 model

In this work, a new class of spectral conjugate gradient (CG) method is proposed for solving unconstrained optimization models. The search direction the uses ZPRP and JYJLL CG coefficients. satisfies descent condition independent line search. global convergence properties under strong Wolfe are proved with some certain assumptions. Based on test functions, numerical experiments presented to show method's efficiency compared other existing methods. application regression models COVID-19 provided. Mathematics subject classification 65K10, 90C52, 90C26.