| 基于粒子群优化的LS-SVM的福建航空物流需求预测 |
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| 引用本文： | 周正勇,林静.基于粒子群优化的LS-SVM的福建航空物流需求预测[J].商品储运与养护,2014(7):52-54. |
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| 作者姓名： | 周正勇 林静 |
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| 作者单位： | 福州大学经济与管理学院,福建福州350108 |
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| 摘 要： | 根据福建省过去十几年航空货物发送量的数据,针对航空物流预测的不确定性,将粒子群优化算法和最小二乘支持向量机相结合,采用粒子群优化最小二乘支持向量机的方法来建立模型。并将优化后的最小二乘支持向量机模型应用于福建省航空物流的需求预测中,而后通过仿真对结果进行验证。
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| 关 键 词： | 粒子群算法 最小二乘支持向量机 航空物流 需求预测 |
The Aviation Logistics Demand Forecast in Fujian Based on Particle Swarm Optimization of LS-SVM |
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| ZHOU Zheng- yong,LIN Jing.The Aviation Logistics Demand Forecast in Fujian Based on Particle Swarm Optimization of LS-SVM[J].Storage Transportation & Preservation of Commodities,2014(7):52-54. |
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| Authors: | ZHOU Zheng- yong LIN Jing |
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| Institution: | (School of Economics and Management,Fuzhou University,Fuzhou 350108 ,China) |
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| Abstract: | According to the data of air freight volume throughout of Fujian in the past decades,considering the uncertainty of the forecast in the aviation logistics demand. A model which use the particle swarm algorithm to optimize the LS- SVM is established,and then applied to predict the aviation logistics demand of Fujian. Finally the results are verified by simulation. |
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| Keywords: | particle swarm optimization LS-SVM aviation logistics demand forecast |
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