•  
  •  
 

Abstract

In this paper, the algorithm (Stochastic Gradient Descent) SGD, which is one of the most famous optimization algorithms, was hybridized with genetic algorithms in finding the roots of non-linear equations, which is one of the most important mathematical problems due to its application in all sciences. Genetic algorithms are used here to find the optimal primary root of SGD algorithm and its application in reducing the studied objective function. Some famous algorithms need initial point to reach the solution in terms of stability. The proposed algorithm is tested on several standard functions and the results are compared with the famous algorithms, and the results show the efficiency of the proposed algorithm through tables and figures.

Keywords

Genetic algorithms, Nonlinear equations, Objective function, Optimizations, SGD algorithm

Subject Area

Mathematics

First Page

273

Last Page

279

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Receive Date

6-1-2022

Revise Date

2-25-2023

Accept Date

2-27-2023

Download

Share

COinS