<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The teaching reform of environmental art design majors is integrated into the rural revitalization strategy, which can best reflect the contemporary characteristics of education and teaching reform. This paper firstly explores and analyzes the significance of education reform of environmental art design majors in colleges and universities under the strategy of rural revitalization and proposes three teaching mode reform measures in combination with the current teaching situation. Secondly, studying the scheduling system based on genetic algorithm which is widely used at present, combines the characteristics of randomness and ergodicity of a chaotic system. Finally, the population diversity, crossover operation and variation operation are improved, thus forming a scheduling algorithm based on a chaotic genetic algorithm, which enables the most reasonable allocation of the existing teaching resources of university environmental design majors. The results show that the maximum running time of the genetic algorithm is 153<italic>t</italic>/<italic>s</italic>, which is much larger than the maximum running time of the chaotic genetic algorithm 57<italic>t</italic>/<italic>s</italic>. The minimum running time of the chaotic genetic algorithm is 19<italic>t</italic>/<italic>s</italic>, which is 23.14% smaller than that of the genetic algorithm. The reform measures proposed in this paper for integrating rural revitalization into teaching provide the optimal and reasonable allocation of teaching resources for the major and employment opportunities for environmental art design students.</p>
</abstract>

The teaching reform of environmental art design majors is integrated into the rural revitalization strategy, which can best reflect the contemporary characteristics of education and teaching reform. This paper firstly explores and analyzes the significance of education reform of environmental art design majors in colleges and universities under the strategy of rural revitalization and proposes three teaching mode reform measures in combination with the current teaching situation. Secondly, studying the scheduling system based on genetic algorithm which is widely used at present, combines the characteristics of randomness and ergodicity of a chaotic system. Finally, the population diversity, crossover operation and variation operation are improved, thus forming a scheduling algorithm based on a chaotic genetic algorithm, which enables the most reasonable allocation of the existing teaching resources of university environmental design majors. The results show that the maximum running time of the genetic algorithm is 153t/s, which is much larger than the maximum running time of the chaotic genetic algorithm 57t/s. The minimum running time of the chaotic genetic algorithm is 19t/s, which is 23.14% smaller than that of the genetic algorithm. The reform measures proposed in this paper for integrating rural revitalization into teaching provide the optimal and reasonable allocation of teaching resources for the major and employment opportunities for environmental art design students.

Research on teaching reform of environmental design majors in colleges and universities based on the integration of rural revitalization into big data

Applied Mathematics and Nonlinear Sciences

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

The teaching reform of environmental art design majors is integrated into the rural revitalization strategy, which can best reflect the contemporary...

Research on teaching reform of environmental design majors in colleges and universities based on the integration of rural revitalization into big data

Pubblicato online: 04 set 2023

Pagine: -

Ricevuto: 12 ott 2022

Accettato: 15 mar 2022

DOI: https://doi.org/10.2478/amns.2023.2.00289

Parole chiave
Rural revitalization, Genetic algorithm, Scheduling system, Variant operation, Chaotic system

© 2023 Xiaomin Xue et al., published by Sciendo

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

Research on teaching reform of environmental design majors in colleges and universities based on the integration of rural revitalization into big data

Pubblicato online: 04 set 2023

Pagine: -

Ricevuto: 12 ott 2022

Accettato: 15 mar 2022

DOI: https://doi.org/10.2478/amns.2023.2.00289

Parole chiaveRural revitalization, Genetic algorithm, Scheduling system, Variant operation, Chaotic system

© 2023 Xiaomin Xue et al., published by Sciendo

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

Parole chiave
Rural revitalization, Genetic algorithm, Scheduling system, Variant operation, Chaotic system