| PSO优化SVM在木材干燥建模中的应用 |
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| 引用本文： | 尹文芳,张冬妍,袁文爽.PSO优化SVM在木材干燥建模中的应用[J].机电产品开发与创新,2010,23(1):97-99. |
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| 作者姓名： | 尹文芳 张冬妍 袁文爽 |
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| 作者单位： | 东北林业大学,黑龙江,哈尔滨,150040 |
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| 基金项目： | 黑龙江省自然科学基金(C200733) |
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| 摘 要： | 在木材干燥计算机控制过程中,基准模型化是此控制过程的必要环节。为提高此建模预测精度,针对SVM木材干燥基准模型的参数进行研究。利用粒子群优化算法中的粒子位置和速度优化此模型参数,并对木材含水率进行预测。仿真实验表明,PSO算法在优化SVM木材干燥基准模型参数方面表现出良好的性能,预测结果具有很高的精度,此模型具有较好的泛化能力和预测能力。
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| 关 键 词： | 粒子群优化 支持向量机 参数优化 木材干燥 |
The Application of PSO Optimization SVM in Wood Drying Modeling |
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| YIN Wen-Fang,ZHANG Dong-Yan,YUAN Wen-Shuang.The Application of PSO Optimization SVM in Wood Drying Modeling[J].Development & Innovation of Machinery & Electrical Products,2010,23(1):97-99. |
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| Authors: | YIN Wen-Fang ZHANG Dong-Yan YUAN Wen-Shuang |
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| Affiliation: | Northeast Forestry University;Harbin Heilongjiang 150040;China |
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| Abstract: | In wood drying process of computer control,the benchmark model is essential.To improve the prediction accuracy,the SVM(support vector machine) of wood drying model parameters were studied.Using the particle position and speed of PSO(particle swarm optimization);algorithm optimizes the model parameters,then to predict the moisture content.Simulation results show that PSO algorithm in optimizing the SVM of wood drying model parameters show good performance,high precision of prediction,and this model has good ... |
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| Keywords: | particle swarm optimization support vector machine the optimized parameters wood drying |
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