Genetic Algorithms for Quadratic Equations

https://doi.org/10.55529/jecnam.35.36.42

Authors

  • Basim K. Abbas Computer Science Department, Collage of Science, Mustansiriyah University, Baghdad, Iraq

Keywords:

Genetic Algorithm, Roots, Fitness Function, Complex Numbers, Quadratic Equation.

Abstract

A common technique for finding accurate solutions to quadratic equations is to employ genetic algorithms. The authors propose using a genetic algorithm to find the complex roots of a quadratic problem. The technique begins by generating a collection of viable solutions, then proceeds to assess the suitability of each solution, choose parents for the next generation, and apply crossover and mutation to the offspring. For a predetermined number of generations, the process is repeated. Comparing the evolutionary algorithm's output to the quadratic formula proves its validity and uniqueness. Furthermore, the utility of the evolutionary algorithm has been demonstrated by programming it in Python code and comparing the outcomes to conventional intuitions.

Published

2023-08-26

How to Cite

Basim K. Abbas. (2023). Genetic Algorithms for Quadratic Equations. Journal of Electronics, Computer Networking and Applied Mathematics , 3(05), 36–42. https://doi.org/10.55529/jecnam.35.36.42

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