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<p>In this paper, after constructing the index system of garden landscape planning, the entropy weight method and hierarchical analysis method are used to combine and assign weights to each index. Using a multi-criterion decision analysis model to establish the decision matrix of landscape planning alternatives, the weighted normative value of each indicator is obtained to obtain the weighted normalization matrix for landscape planning. According to the matrix analysis to get the positive and negative ideal solution of each index, calculate the utility function value between each alternative and the perfect solution, and get the optimal decision-making scheme of landscape planning. The analysis of the three options for landscape planning found that Scheme S2 has the largest utility function value of 0.642, which is considered the optimal scheme. The analysis of the application effect of this scheme found that the proportion of garden green space in the Xinghua garden landscape area increased by 16.23 % compared with 2010, and the proportion of enterprise and institutional land decreased by 5.04 %. The analysis results of this paper show that the multi-criteria decision analysis model plays a highly supportive role in the decision-making of landscape planning, and lays a foundation for the decision-making of the optimal scheme in future landscape planning.</p>
</abstract>

In this paper, after constructing the index system of garden landscape planning, the entropy weight method and hierarchical analysis method are used to combine and assign weights to each index. Using a multi-criterion decision analysis model to establish the decision matrix of landscape planning alternatives, the weighted normative value of each indicator is obtained to obtain the weighted normalization matrix for landscape planning. According to the matrix analysis to get the positive and negative ideal solution of each index, calculate the utility function value between each alternative and the perfect solution, and get the optimal decision-making scheme of landscape planning. The analysis of the three options for landscape planning found that Scheme S2 has the largest utility function value of 0.642, which is considered the optimal scheme. The analysis of the application effect of this scheme found that the proportion of garden green space in the Xinghua garden landscape area increased by 16.23 % compared with 2010, and the proportion of enterprise and institutional land decreased by 5.04 %. The analysis results of this paper show that the multi-criteria decision analysis model plays a highly supportive role in the decision-making of landscape planning, and lays a foundation for the decision-making of the optimal scheme in future landscape planning.

The practice of multi-criteria decision analysis modeling in decision support for landscape planning

China University of Mining and Technology

Applied Mathematics and Nonlinear Sciences

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

In this paper, after constructing the index system of garden landscape planning, the entropy weight method and hierarchical analysis method are used to combine...

The practice of multi-criteria decision analysis modeling in decision support for landscape planning

Publié en ligne: 03 juin 2024

Pages: -

Reçu: 06 mars 2024

Accepté: 07 mai 2024

DOI: https://doi.org/10.2478/amns-2024-1340

Mots clés
Multi-criteria decision analysis, Indicator weights, Entropy weighting method, Hierarchical analysis, Landscape planning

© 2024 Yiwen Xu, et al., published by Sciendo

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

The practice of multi-criteria decision analysis modeling in decision support for landscape planning

Publié en ligne: 03 juin 2024

Pages: -

Reçu: 06 mars 2024

Accepté: 07 mai 2024

DOI: https://doi.org/10.2478/amns-2024-1340

Mots clésMulti-criteria decision analysis, Indicator weights, Entropy weighting method, Hierarchical analysis, Landscape planning

© 2024 Yiwen Xu, et al., published by Sciendo

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

Mots clés
Multi-criteria decision analysis, Indicator weights, Entropy weighting method, Hierarchical analysis, Landscape planning