Forecasting population based on support vector regression with intelligent genetic algorithms

doi:10.3778/j.issn.1002-8331.2008.21.003

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (21): 9-11.DOI: 10.3778/j.issn.1002-8331.2008.21.003

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Forecasting population based on support vector regression with intelligent genetic algorithms

DAI Hong-liang^1,2

1.Department of Mathematics and Computational Science，Guangdong University of Business Studies，Guangzhou 510320，China
2.Department of Mathematics，Sun Yat-Sen（Zhongshan） University，Guangzhou 510275，China

Received:2008-03-24 Revised:2008-04-17 Online:2008-07-21 Published:2008-07-21
Contact: DAI Hong-liang

基于智能遗传算法与支持向量回归的人口预测

戴宏亮^1,2

1.广东商学院数学与计算科学学院，广州 510320
2.中山大学数学与计算科学学院，广州 510275

通讯作者: 戴宏亮

Abstract

Abstract: To build an effective SVR model，SVR’s parameters must be set carefully.This study proposes a novel approach，known as IGASVR，which searches for SVR’s optimal parameters using intelligent genetic algorithms，and then adopts the optimal parameters to construct the SVR models.Finally we apply IGASVR to forecast population.The experimental results demonstrates that IGASVR are better than standard SVR and BP neural-network.IGASVR model is an effective approach which has faster speed of training and higher precision.

Key words: Support Vector Regression, intelligent genetic algorithms, population, forecasting

摘要： 要建立一个有效的支持向量回归（SVR）模型，支持向量回归的3个参数C，γ，ε必须预先设定。提出一种新型的遗传算法——智能遗传算法（IGA）对支持向量回归进行参数调节，以达到寻找最优参数的目的，然后和支持向量回归结合得到一种新的IGASVR模型，并应用于城市人口预测。最后，将提出的方法与标准SVR模型和BP神经网络模型进行比较，所得结果表明，该模型训练速度快，并且有较高预测精度，是一种有效的人口预测方法。

关键词: 支持向量回归, 智能遗传算法, 人口, 预测

DAI Hong-liang^1,2. Forecasting population based on support vector regression with intelligent genetic algorithms[J]. Computer Engineering and Applications, 2008, 44(21): 9-11.

戴宏亮^1,2. 基于智能遗传算法与支持向量回归的人口预测[J]. 计算机工程与应用, 2008, 44(21): 9-11.

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Forecasting population based on support vector regression with intelligent genetic algorithms

基于智能遗传算法与支持向量回归的人口预测

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