Research on optimization of ecological restoration design scheme using genetic algorithm

Xiaoxi Tang

doi:10.1117/12.3056016

9 January 2025 Research on optimization of ecological restoration design scheme using genetic algorithm

Xiaoxi Tang

Author Affiliations +

Proceedings Volume 13486, Fourth International Conference on Computer Vision, Application, and Algorithm (CVAA 2024); 134862Z (2025) https://doi.org/10.1117/12.3056016
Event: Fourth International Conference on Computer Vision, Application, and Algorithm (CVAA 2024), 2024, Chengdu, China

Abstract

In order to improve the optimization effect of ecological restoration design scheme, genetic algorithm is used in this study and compared with simulated annealing and particle swarm optimization methods. By comparing the convergence speed and optimization effect of each method, the results show that the genetic algorithm is better than other methods in terms of convergence speed and optimization effect. The experimental data demonstrated the trend of the fitness of the genetic algorithm in multiple iterations, as well as the influence of different parameter settings on the optimization effect. The study verifies the effectiveness and superiority of genetic algorithm in ecological restoration design, which provides a powerful optimization tool and theoretical support for the solution of complex ecological problems.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiaoxi Tang "Research on optimization of ecological restoration design scheme using genetic algorithm", Proc. SPIE 13486, Fourth International Conference on Computer Vision, Application, and Algorithm (CVAA 2024), 134862Z (9 January 2025); https://doi.org/10.1117/12.3056016

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