| 预测AL2O3粒子衰减特性的LSSVM方法 |
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| 引用本文： | 王雁鸣.预测AL2O3粒子衰减特性的LSSVM方法[J].南京邮电大学学报(自然科学版),2009,9(18). |
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| 作者姓名： | 王雁鸣 |
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| 作者单位： | 哈尔滨工业大学能源科学与工程学院 |
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| 基金项目： | 国家自然科学基金项目（面上项目，重点项目，重大项目） |
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| 摘 要： | 应用最小二乘支持向量机建立了AL2O3粒子衰减特性预测模型，引入微粒群算法解决了模型多参数优化问题，结合辐射传输数值求解方法获得了吸收散射性介质的红外辐射特性。比较结果表明，该方法具有较好的预测能力，在保证模拟结果精度的同时提高了运算速度。
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| 收稿时间： | 6/18/2009 3:07:56 PM |
| 修稿时间： | 6/18/2009 3:07:56 PM |
Prediction for Extinction Property of AL2O3 Particle by LSSVM Method |
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| Wang Yan-Ming.Prediction for Extinction Property of AL2O3 Particle by LSSVM Method[J].Journal of Nanjing University of Posts and Telecommunications,2009,9(18). |
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| Authors: | Wang Yan-Ming |
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| Abstract: | A prediction model for extinction property of AL2O3 particle was established by using least square support vector machine. Particle swarm optimization method was applied to optimize the multi-parameters. Combined with the numerical method for radiative heat transfer, the infrared properties of emitting and scattering medium were obtained. The result shows that the method in this paper is capable to predict the extinction property accurately meanwhile the operation rate has great enhancement. |
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