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DOI: 10.14569/IJACSA.2023.01408123
PDF

Rural Landscape Design Data Analysis Based on Multi-Media, Multi-Dimensional Information Based on a Decision Tree Learning Algorithm

Author 1: Ning Leng
Author 2: Hongxin Wang

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 8, 2023.

  • Abstract and Keywords
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Abstract: This paper analyzes and studies the design characteristics of multi-dimensional information rural scenes. For data mining and the Decision Tree (DT) calculation method, the pre-processing system and method of multi-dimensional information rural award design are put forward again. Through the analysis of the multi-dimensional value of multi-dimensional multimedia mountain villages, the form of planning and design analysis and corresponding methods are based on the analysis. Using one village as a case study, we were able to investigate the villagers, roads, services, greening, ecology, and other aspects of the village in complete detail and then implement the multi-media, multi-resource village's detailed planning and design.

Keywords: Multi-media multi-dimensional information rural landscape; data mining; decision tree; data preprocessing

Ning Leng and Hongxin Wang. “Rural Landscape Design Data Analysis Based on Multi-Media, Multi-Dimensional Information Based on a Decision Tree Learning Algorithm”. International Journal of Advanced Computer Science and Applications (IJACSA) 14.8 (2023). http://dx.doi.org/10.14569/IJACSA.2023.01408123

@article{Leng2023,
title = {Rural Landscape Design Data Analysis Based on Multi-Media, Multi-Dimensional Information Based on a Decision Tree Learning Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.01408123},
url = {http://dx.doi.org/10.14569/IJACSA.2023.01408123},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {8},
author = {Ning Leng and Hongxin Wang}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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