| 我国专利申请量的支持向量机预测模型研究 |
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| 引用本文： | 徐晟,赵惠芳,郭雪松.我国专利申请量的支持向量机预测模型研究[J].运筹与管理,2007,16(5):137-141. |
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| 作者姓名： | 徐晟 赵惠芳 郭雪松 |
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| 作者单位： | 1. 合肥工业大学,管理学院,安徽,合肥,230009
2. 西安交通大学,管理学院,陕西,西安,710049 |
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| 基金项目： | 国家自然科学基金;国家社会科学基金 |
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| 摘 要： | 运用支持向量机(support vector machine,SVM)和浮点遗传算法相结合的方法对我国专利申请量进行预测。数据仿真显示支持向量机预测方法比人工神经网络和逻辑回归方法有更高的预测精度,结果显示运用浮点遗传算法参数选取的支持向量机方法对我国专利申请量进行预测是可行和有效的。
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| 关 键 词： | 预测 模型 支持向量机 专利申请量 |
| 文章编号： | 1007-3221（2007）05-0137-05 |
| 修稿时间： | 2007-05-10 |
A Support Vector Machine Model for Patent Application Quantities Forecast in China |
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| XU Sheng,ZHAO Hui-fang,GUO Xue-song.A Support Vector Machine Model for Patent Application Quantities Forecast in China[J].Operations Research and Management Science,2007,16(5):137-141. |
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| Authors: | XU Sheng ZHAO Hui-fang GUO Xue-song |
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| Abstract: | A forecasting system of patent application quantities is studied by means of applying the support vector machine(SVM) and float-point genetic algorithms.It has higher forecasting precision and stronger generalization ability to forecast applied patent quantities than artificial neural network(ANN)and logistic regression.The results show that the proposed method is feasible and effective. |
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| Keywords: | forecasting model support vector machine(SVM) patent application quantities |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
