| 基于PCA改进的LS-SVM入境旅游客流量预测模型 |
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| 引用本文： | 张朝元,杨泽恒,王彭德,陈丽.基于PCA改进的LS-SVM入境旅游客流量预测模型[J].科技通报,2012,28(7):75-79. |
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| 作者姓名： | 张朝元 杨泽恒 王彭德 陈丽 |
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| 作者单位： | 1. 大理学院数学与计算机学院,云南大理,671003
2. 大理学院工程学院,云南大理,671003 |
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| 基金项目： | 云南省教育厅科学研究基金项目 |
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| 摘 要： | 影响入境旅游客流量的众多因素加大了预测模型输入变量的复杂化,限制了模型的运行速度和预测精确。首先,利用主成分分析对影响入境旅游客流量的众多指标进行综合分析得到主成分,然后建立以主成分为输入变量以入境旅游客流量为输出变量的最小二乘支持向量机预测模型。通过实例验证和比较,展示了基于主成分分析改进的最小二乘支持向量机入境旅游客流量预测模型具有较好的预测效果和较高的推广价值。
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| 关 键 词： | 入境旅游客流量 主成分分析 最小二乘支持向量机 预测模型 |
The Forecast Model of Tourist Flow of Entering based on LS-SVM Improved by Principal Component Analysis |
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| ZHANG Chaoyuan
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YANH Zeheng
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WANG Pengde
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CHEN Li.The Forecast Model of Tourist Flow of Entering based on LS-SVM Improved by Principal Component Analysis[J].Bulletin of Science and Technology,2012,28(7):75-79. |
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| Authors: | ZHANG Chaoyuan YANH Zeheng WANG Pengde CHEN Li |
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| Institution: | 1.College of Mathematics and Computer,Dali University,Dali,Yunnan 671003 China; 2.College of Engineering,Dali University,Dali,Yunnan 671003,China) |
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| Abstract: | Many factors influencing tourist flow of entering increase the complexity of the input variables and limit speed and precision of prediction model.Firstly,the main components are gained through analyzing the impact indicators of tourist flow of entering using principal component analysis.Secondly,it is established the forecast model of Least Squares Support Vector Machine based on input variables of main components and output variable of tourist flow.Through example confirmation and comparison,it is showed that good forecast effect and high application value of the forecast model of tourist flow of entering based on Least Squares Support Vector Machine improved by principal component analysis. |
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| Keywords: | tourist flow of entering principal component analysis least squares support vector machine forecast model |
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