NSOIA

A Fortran subroutine for solving systems of nonlinear algebraic equations. A Fortran subroutine is described and listed for solving a system of non-linear algebraic equations. The method used to obtain the solution to the equations is a compromise between the Newton-Raphson algorithm and the method of steepest descents applied to minimize the function noted, for the aim is to combine a fast rate of convergence with steady progress. Some examples illustrate the technique, and they indicate that the given algorithm compares favorable with other numerical methods for solving non-linear equations. .. The name of the subroutine and its parameters are: SUBROUTINE NS01A (N,X,F,AJINV,DSTEP,DMAX,AOC,MAXFUN,IPRINT,W)


References in zbMATH (referenced in 40 articles , 1 standard article )

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  1. Demange, Simon; Chazot, O.; Pinna, F.: Local analysis of absolute instability in plasma jets (2020)
  2. Javaherian, A.; Lucka, F.; Cox, B. T.: Refraction-corrected ray-based inversion for three-dimensional ultrasound tomography of the breast (2020)
  3. Liu, Ching-Sung: A positivity preserving iterative method for finding the ground states of saturable nonlinear Schrödinger equations (2020)
  4. Ji, Hangjie; Li, Longfei: Numerical methods for thermally stressed shallow shell equations (2019)
  5. Bouda, Martin; Brodersen, Craig; Saiers, James: Whole root system water conductance responds to both axial and radial traits and network topology over natural range of trait variation (2018)
  6. Fang, Xiaowei; Ni, Qin; Zeng, Meilan: A modified quasi-Newton method for nonlinear equations (2018)
  7. Peherstorfer, Benjamin; Willcox, Karen; Gunzburger, Max: Survey of multifidelity methods in uncertainty propagation, inference, and optimization (2018)
  8. Best, Gabriela: A New Keynesian model with staggered price and wage setting under learning (2015)
  9. Chen, Chunguang; Hattori, Harumi: Exact Riemann solvers for conservation laws with phase change (2015)
  10. La Cruz, William: Simulation of the oxygen distribution in a tumor tissue using residual algorithms (2015)
  11. Sayed Hassen, S. Z.: Modelling, analysis and simulation of an optical squeezer (2015)
  12. Yuan, Ya-xiang: Recent advances in trust region algorithms (2015)
  13. Erway, Jennifer B.; Marcia, Roummel F.: Algorithm 943: MSS: MATLAB software for L-BFGS trust-region subproblems for large-scale optimization (2014)
  14. Pettersson, Per; Iaccarino, Gianluca; Nordström, Jan: A stochastic Galerkin method for the Euler equations with roe variable transformation (2014)
  15. Chen, X.; Akella, S.; Navon, I. M.: A dual-weighted trust-region adaptive POD 4-D var applied to a finite-volume shallow water equations model on the sphere (2012)
  16. Erway, Jennifer B.; Marcia, Roummel F.: Limited-memory BFGS systems with diagonal updates (2012)
  17. Hernández, Janko; Saunders, David; Seco, Luis: Algorithmic estimation of risk factors in financial markets with stochastic drift (2012)
  18. Papakonstantinou, Joanna M.; Tapia, Richard A.: Generation of classes of symmetric rank-2 secant updates and the maximality of the Davidon class (2012)
  19. Shterenlikht, A.; Alexander, N. A.: Levenberg-Marquardt vs Powell’s dogleg method for Gurson-Tvergaard-Needleman plasticity model (2012)
  20. Gorczyca, Mateusz; Janiak, Adam: Resource level minimization in the discrete-continuous scheduling (2010)

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