| 基于BP神经网络的牡丹花热风干燥含水率预测模型 |
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| 引用本文： | 朱文学,孙淑红,陈鹏涛,陈志宏. 基于BP神经网络的牡丹花热风干燥含水率预测模型[J]. 农业机械学报, 2011, 42(8): 128-130,137 |
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| 作者姓名： | 朱文学 孙淑红 陈鹏涛 陈志宏 |
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| 作者单位： | 河南科技大学食品与生物工程学院,洛阳,471003 |
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| 基金项目： | 河南省杰出青年基金资助项目（084100510005）;洛阳市科技攻关项目（0901048） |
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| 摘 要： | 针对热风干燥制作牡丹压花时含水率不便实时测定的问题,探讨了干燥过程中热风温度、风速、压花板孔密度和牡丹花初始质量对干燥速率的影响.利用BP神经网络建立了干燥时间、热风温度、风速、牡丹花初始质量、压花板孔密度与牡丹花干燥过程中含水率之间的关系模型,采用Matlab神经网络工具箱对模型参数进行训练和模拟.结果表明,利用神经网络建立的模型仿真结果与实测值接近,预测性较好.
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| 关 键 词： | 牡丹花 干燥 含水率 预测模型 BP神经网络 |
Moisture Content Prediction Modeling of Hot-air Drying for Pressed Peony Based on BP Neural Network |
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| Zhu Wenxue,Sun Shuhong,Chen Pengtao and Chen Zhihong. Moisture Content Prediction Modeling of Hot-air Drying for Pressed Peony Based on BP Neural Network[J]. Transactions of the Chinese Society for Agricultural Machinery, 2011, 42(8): 128-130,137 |
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| Authors: | Zhu Wenxue Sun Shuhong Chen Pengtao Chen Zhihong |
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| Affiliation: | Henan University of Science and Technology;Henan University of Science and Technology;Henan University of Science and Technology;Henan University of Science and Technology |
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| Abstract: | Pressed peony was made by hot-air drying method. The influence of temperature of hot-air, speed of hot-air, drying board's hole density and the initial mass of peony on drying speed was discussed. Relationship model between drying time, temperature of hot-air, speed of hot-air, drying board's hole density, the initial mass and moisture content was built by using BP neural network. Parameters in the proposed model were trained and simulated in Matlab. The results indicated that the simulated values of the drying moisture content were close to the measured values. |
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| Keywords: | Peony Drying Moisture content Prediction model BP neural network |
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