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<p>This paper presents a coupled evaluation of rural habitat environment as well as rural tourism in China based on a multi-objective optimization algorithm. Firstly, the ANN model is used as the three objective evaluation function values of CVBEC, LCC and LCCO2 as the dependent variables, and the NSGA-II algorithm is introduced as the optimization algorithm for the multi-objective optimization of rural architectural design. Secondly, based on the ANN-NSGA-II algorithm, an improvement strategy is proposed for the rural building environment algorithm, and the multi-objective discrete particle swarm algorithm with a dominant ranking number is applied to rural tourism route planning. Then the coupled evaluation system of rural habitat environment and rural tourism is constructed by first and second-level indicators. Finally, the coordination degree and spatial autocorrelation analysis of the multi-system coupling relationship are conducted for the coupling evaluation system. The study shows that the coordinated development degree P value increased from 0.02 in 2017 to 0.83 in 2022, Moran’s I index of living environment and ecological environment system is greater than 0, and the Z value is greater than 1.63.</p>
</abstract>

This paper presents a coupled evaluation of rural habitat environment as well as rural tourism in China based on a multi-objective optimization algorithm. Firstly, the ANN model is used as the three objective evaluation function values of CVBEC, LCC and LCCO2 as the dependent variables, and the NSGA-II algorithm is introduced as the optimization algorithm for the multi-objective optimization of rural architectural design. Secondly, based on the ANN-NSGA-II algorithm, an improvement strategy is proposed for the rural building environment algorithm, and the multi-objective discrete particle swarm algorithm with a dominant ranking number is applied to rural tourism route planning. Then the coupled evaluation system of rural habitat environment and rural tourism is constructed by first and second-level indicators. Finally, the coordination degree and spatial autocorrelation analysis of the multi-system coupling relationship are conducted for the coupling evaluation system. The study shows that the coordinated development degree P value increased from 0.02 in 2017 to 0.83 in 2022, Moran’s I index of living environment and ecological environment system is greater than 0, and the Z value is greater than 1.63.

Construction of a coupled evaluation index system of rural habitat environment and rural tourism in China based on multi-objective optimization algorithm

Applied Mathematics and Nonlinear Sciences

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

This paper presents a coupled evaluation of rural habitat environment as well as rural tourism in China based on a multi-objective optimization algorithm....

Construction of a coupled evaluation index system of rural habitat environment and rural tourism in China based on multi-objective optimization algorithm

Publicado en línea: 11 oct 2023

Páginas: -

Recibido: 29 oct 2022

Aceptado: 21 abr 2023

DOI: https://doi.org/10.2478/amns.2023.2.00601

Palabras clave
Multi-objective optimization algorithm, ANN-NSGA-II algorithm, Rural habitat environment, Rural tourism, Coupled evaluation

© 2023 Xiaojing Liu, published by Sciendo

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

Construction of a coupled evaluation index system of rural habitat environment and rural tourism in China based on multi-objective optimization algorithm

Publicado en línea: 11 oct 2023

Páginas: -

Recibido: 29 oct 2022

Aceptado: 21 abr 2023

DOI: https://doi.org/10.2478/amns.2023.2.00601

Palabras claveMulti-objective optimization algorithm, ANN-NSGA-II algorithm, Rural habitat environment, Rural tourism, Coupled evaluation

© 2023 Xiaojing Liu, published by Sciendo

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

Palabras clave
Multi-objective optimization algorithm, ANN-NSGA-II algorithm, Rural habitat environment, Rural tourism, Coupled evaluation