| 基于支持向量机的丙酮精制建模 |
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| 引用本文： | 王鹏,王雄,熊智华. 基于支持向量机的丙酮精制建模[J]. 微计算机信息, 2006, 22(27): 1-2 |
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| 作者姓名： | 王鹏 王雄 熊智华 |
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| 作者单位： | 100084,北京,清华大学 |
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| 基金项目： | 国家自然科学基金(60404012) |
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| 摘 要： | 采用支持向量机建立了丙酮精制过程的产品质量与生产工艺参数之间的预测模型,并将其与反向传播神经网络和径向基神经网络模型相比较。在实际工业数据上进行的实验结果表明,支持向量机模型对丙酮纯度具有良好的预测效果,性能优于反向传播神经网络和径向基网络模型。
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| 关 键 词： | 支持向量机 神经网络 丙酮精制 |
| 文章编号： | 1008-0570(2006)09-3-0001-02 |
| 修稿时间： | 2006-01-25 |
Modeling Acetone Refining Process Based on Support Vector Machine |
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| Wang,Peng,Wang,Xiong,Xiong,Zhihua. Modeling Acetone Refining Process Based on Support Vector Machine[J]. Control & Automation, 2006, 22(27): 1-2 |
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| Authors: | Wang Peng Wang Xiong Xiong Zhihua |
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| Abstract: | Support vector machine (SVM) is applied to build a prediction model of the acetone quality in an industrial acetone refining process. The model is also compared with the models based on back- propagation neural network (BPNN) and radial basis function neural network (RBFNN). The experimental results on the real industrial data demonstrate that the model based on SVM achieves good performance and has less prediction errors than those of BPNN and RBFNN models. |
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| Keywords: | support vector machine neural network acetone refining process |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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