Computer graphic display of gross domestic product development in Shixing County based on decision tree structure, RANSAC algorithm, and Ridge Regression algorithm
Authors: 
Lidong Liu, Keer Zhou, Xiaoqin Li, Yongbin Luo, Rong Zhang, Rui Huang, Jinghui Feng, Ziyu ChenAuthors Info & Claims
Lidong Liu, Keer Zhou, Xiaoqin Li, Yongbin Luo, Rong Zhang, Rui Huang, Jinghui Feng, Ziyu ChenAuthors Info & ClaimsPages 1057 - 1061
Abstract
Computer graphics can present data and information in an intuitive and visual way, enabling decision-makers to understand and analyze complex datasets more quickly. By transforming data into visual forms such as charts and images, patterns and trends in the data can be revealed, helping decision-makers discover hidden information and associations, thereby improving decision-making efficiency and accuracy. This study utilized the GDP data of Shixing County, Shaoguan City, Guangdong Province from 2007 to 2023, and used decision tree algorithm to generate a GDP decision tree architecture diagram to understand the process of GDP changes in Shixing County and the connection relationship between various samples. Subsequently, using RANSAC and Ridge Regression algorithms, a development trend chart was drawn to make the data and information more attractive and persuasive. Ultimately, this data can provide valuable references for local development.
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Index Terms
- Computer graphic display of gross domestic product development in Shixing County based on decision tree structure, RANSAC algorithm, and Ridge Regression algorithm
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Published In
June 2024
1206 pages
ISBN:9798400710247
DOI:10.1145/3690407
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Association for Computing Machinery
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Published: 24 October 2024
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CAIBDA 2024
CAIBDA 2024: 2024 4th International Conference on Artificial Intelligence, Big Data and Algorithms
June 21 - 23, 2024
Zhengzhou, China
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