A Decision Tree Analysis Approach to Traditional and Modern Design Elements in Rural Landscaping

According to the connotation of traditional and modern design elements in rural landscape beautification, multi-dimensional data cube mining method is adopted to construct the research data set of this paper.According to the ratio of 2:8, the data set is divided into test set and training set.The data of traditional and modern design elements are used as inputs, substituted into the decision tree model for training and classification, and the CART algorithm is used to construct a decision tree model for traditional and modern design elements in rural landscape beautification.Combining the dataset and the model in this paper, the simulation analysis of traditional and modern design elements in rural landscape beautification is carried out.The data show that based on the Gini index calculation formula of CART algorithm, it is concluded that the Gini index of X9 (0.9581) is the largest, so X9 is chosen as the root node for decision making, and the decision tree is derived downward until the leaf node, and the decision tree oriented to the countryside landscaping is obtained, and the rural landscape beautification scheme is induced based on the results of the analysis and the effect of the rural landscaping is found to have the difference between the before and after mean values of 3.36 ( 20.11-16.75=3.36),while there is a significant difference between the two, similarly, there is also a significant difference in the building living comfort above.This study enhances the effect of rural landscape beautification, which is of great significance in promoting rural revitalisation and architectural design development.

Publication Details

Journal
Journal of Combinatorial Mathematics and Combinatorial Computing
Published
2025-04-16
DOI
https://doi.org/10.61091/jcmcc127a-152
Primary Topic
Korean Urban and Social Studies
Type
article
Field-Weighted Citation Impact
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article

A Decision Tree Analysis Approach to Traditional and Modern Design Elements in Rural Landscaping

Journal of Combinatorial Mathematics and Combinatorial Computing
Korean Urban and Social Studies
article

A Decision Tree Analysis Approach to Traditional and Modern Design Elements in Rural Landscaping

article en

Abstract

According to the connotation of traditional and modern design elements in rural landscape beautification, multi-dimensional data cube mining method is adopted to construct the research data set of this paper.According to the ratio of 2:8, the data set is divided into test set and training set.The data of traditional and modern design elements are used as inputs, substituted into the decision tree model for training and classification, and the CART algorithm is used to construct a decision tree model for traditional and modern design elements in rural landscape beautification.Combining the dataset and the model in this paper, the simulation analysis of traditional and modern design elements in rural landscape beautification is carried out.The data show that based on the Gini index calculation formula of CART algorithm, it is concluded that the Gini index of X9 (0.9581) is the largest, so X9 is chosen as the root node for decision making, and the decision tree is derived downward until the leaf node, and the decision tree oriented to the countryside landscaping is obtained, and the rural landscape beautification scheme is induced based on the results of the analysis and the effect of the rural landscaping is found to have the difference between the before and after mean values of 3.36 ( 20.11-16.75=3.36),while there is a significant difference between the two, similarly, there is also a significant difference in the building living comfort above.This study enhances the effect of rural landscape beautification, which is of great significance in promoting rural revitalisation and architectural design development.

Journal of Combinatorial Mathematics and Combinatorial ComputingVol. 127a
Sustainable cities and communities
Openalex Percentile: Top 88%
Korean Urban and Social Studies
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