| 基于LS-SVM的小样本费用智能预测 |
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| 引用本文： | 张晓晖,朱家元,张恒喜.基于LS-SVM的小样本费用智能预测[J].计算机工程与应用,2004,40(27):203-204,214. |
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| 作者姓名： | 张晓晖 朱家元 张恒喜 |
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| 作者单位： | 1. 西安交通大学MPA中心,西安,710049
2. 空军工程大学工程学院飞机与发动机工程系,西安,710038 |
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| 基金项目： | 国家部委项目，空军重点型号工程项目资助 |
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| 摘 要： | 最小二乘支持向量机引入最小二乘线性系统到支持向量机中,代替传统的支持向量机采用二次规划方法解决函数估计问题。该文推导了用于函数估计的最小二乘支持向量机算法,构建了基于最小二乘支持向量机的智能预测模型,并对机载电子设备费用预测进行了研究。结果表明最小二乘支持向量机具有比多元对数回归更高的小样本费用预测精度。
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| 关 键 词： | 机器学习 支持向量机 神经网络 最小二乘支持向量机 小样本预测 |
| 文章编号： | 1002-8331-(2004)27-0203-02 |
Cost Intelligent Prediction with Few Observations Using Least Squares Support Vector Machines |
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| Zhang Xiaohui,Zhu Jiayuan,Zhang Hengxi.Cost Intelligent Prediction with Few Observations Using Least Squares Support Vector Machines[J].Computer Engineering and Applications,2004,40(27):203-204,214. |
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| Authors: | Zhang Xiaohui Zhu Jiayuan Zhang Hengxi |
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| Affiliation: | Zhang Xiaohui 1 Zhu Jiayuan 2 Zhang Hengxi 21 |
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| Abstract: | Least squares support vector machines(LS-SVM)is a novel support vector machines for function estimation even with small samples.Due to equality type constraints in the formulation,the solution follows from solving a set of linear equations instead of quadratic programming for classical SVM.This paper approaches a data prediction model based on the LS-SVM.Avionics equipment costs are predicted with the intelligent model.The results show that the model has excellent learning ability and generalization,and can provide more accurate data prediction only with few observed samples compared with regression method. |
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| Keywords: | machine learning support vector machines neural networks least squares support vector machines prediction with few observations |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
