Smart Growth Modeling and Prediction Based on Principle Component Analysis and Support Vector Regression

Cai Nian; Li Fei-yang; Chen Wen-jie; Chen Wei-jian

doi:10.12052/gdutxb.170073

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Smart Growth Modeling and Prediction Based on Principle Component Analysis and Support Vector Regression

更新时间：2026-05-27

- Smart Growth Modeling and Prediction Based on Principle Component Analysis and Support Vector Regression
- Vol. 34, Issue 5, Pages: 29-33(2017)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.12052/gdutxb.170073
  CLC： TP391.9
- Published：2017
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蔡念, 李飞洋, 陈文杰, 陈伟建. 基于主成分分析与支持向量回归的精明增长建模与预测[J]. 广东工业大学学报, 2017, 34(5): 29-33.

Cai Nian, Li Fei-yang, Chen Wen-jie, et al. Smart Growth Modeling and Prediction Based on Principle Component Analysis and Support Vector Regression[J]. 2017, 34(5): 29-33.
蔡念, 李飞洋, 陈文杰, 陈伟建. 基于主成分分析与支持向量回归的精明增长建模与预测[J]. 广东工业大学学报, 2017, 34(5): 29-33. DOI： 10.12052/gdutxb.170073.

Cai Nian, Li Fei-yang, Chen Wen-jie, et al. Smart Growth Modeling and Prediction Based on Principle Component Analysis and Support Vector Regression[J]. 2017, 34(5): 29-33. DOI： 10.12052/gdutxb.170073.

摘要

随着城市化的迅速蔓延，如何使城市可持续化发展成为当前政府决策者的重要议题.为了有效地制定精明增长的策略，本文提出一种基于主成分分析的评价模型量化精明增长的程度；建立支持向量回归模型预测影响精明增长的各个指标的年际变化趋势，计算未来精明增长的预计得分；通过预计得分值选择最佳的精明增长计划方案.实验表明，该模型能准确地衡量精明增长的程度，并且能对未来的精明增长做出预测，从而为城市的合理健康发展提供决策指导.

Abstract

With the urbanization extending at a high speed

the sustainable development of cities becomes a significant agenda for government policy makers. In order to effectively develop the strategy of smart growth

an evaluation model is proposed. First

principle component analysis (PCA) is applied to quantify the level of smart growth. Then

support vector regression (SVR) is employed to predict annual variation tendency of each indicator of smart growth. Finally

the total scores of smart growth are calculated for selecting an optimal solution to smart growth. The experiment results show that the proposed evaluation model can accurately measure the level of smart growth and predict the situation of smart growth in the future

which provides a comprehensive decision guidance for rational and healthy development of cities.

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references

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