基于神经网络的出菇房CFD温度均匀性预测模型
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摘要
为预测出菇房内环境性能指标,采用CFD建立菇房模型并通过试验数据验证仿真结果准确性,对比可知温度的平均相对误差为4.9%,引入温度均匀性指标,设计正交试验进行CFD数值模拟,利用模拟数据训练GMDH(group method of data handling,数据处理组合法)型神经网络,最后得出温度均匀性指标的预测模型。分析结果表明,预测值与CFD仿真值相关系数达到0.942 5,平均绝对误差仅为0.042,预测精度较高,为出菇房的进一步优化提供可靠依据。
Aiming at predicting the environmental performance index of mushroom house, CFD is used to establish the model and the accuracy of the simulation results is verified by comparing with experimental data. The average relative error of the temperature is 4.9%. The temperature uniformity index is introduced and the orthogonal test is designed for CFD numerical simulation. Using the simulation data to train the GMDH(group method of data handling) type neural network, and finally obtains the prediction model of the temperature uniformity index. The analysis results show that prediction accuracy of GMDH type neural network is high enough. Because it can be seen that the correlation coefficient between the predicted value and CFD simulation value reaches 0.942 5 and the average absolute error is only 0.042 K. It can provide a reliable basis for further optimization of the mushroom house.
Aiming at predicting the environmental performance index of mushroom house, CFD is used to establish the model and the accuracy of the simulation results is verified by comparing with experimental data. The average relative error of the temperature is 4.9%. The temperature uniformity index is introduced and the orthogonal test is designed for CFD numerical simulation. Using the simulation data to train the GMDH(group method of data handling) type neural network, and finally obtains the prediction model of the temperature uniformity index. The analysis results show that prediction accuracy of GMDH type neural network is high enough. Because it can be seen that the correlation coefficient between the predicted value and CFD simulation value reaches 0.942 5 and the average absolute error is only 0.042 K. It can provide a reliable basis for further optimization of the mushroom house.
引文
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[16] Atashrouz S,Pazuki G,Kakhki S S.A GMDH-type neural network for prediction of water activity in glycol and Poly(ethylene glycol) solutions [J].Journal of Molecular Liquids,2015,202(202):95-100.
[17] 刘艳阳,崔亮,张晔,等.基于COMSOL的马铃薯原料库置换通风系统仿真与分析[J].中国农机化学报,2018,39(10):65-70.Liu Yanyang,Cui Liang,Zhang Ye,et al.Simulation and analysis of displacement ventilation system for potato raw material storage based on COMSOL [J].Journal of Chinese Agricultural Mechanization,2018,39(10):65-70.
[2] 韩清华,李树君,张云川,等.食用菌工厂化栽培环境的远程监测系统[J].农业机械学报,2008,39(8):123-127.
[3] Mat I,Kassim M R M,Harun A N,et al.Environment control for smart mushroom house [C].2017 IEEE Conference on Open Systems (ICOS),IEEE,2017:38-42.
[4] 周轲,王瑞华,孙海亭,等.CFD模拟两种风机位置的苹果冷藏库的温度场[J].中国农机化学报,2016,37(7):75-79.Zhou Ke,Wang Ruihua,Sun Haiting,et al.Simulation of the temperature field of the two fan solution in cool store based on CFD [J].Journal of Chinese Agricultural Mechanization,2016,37(7):75-79.
[5] 赵杰强,赵云.机械通风连栋温室的温度场CFD模拟[J].中国农机化学报,2014,35(6):76-79.Zhao Jieqiang,Zhao Yun.Computational fluid dynamics simulation on temperature field of mechanical ventilation for muti-span greenhouse [J].Journal of Chinese Agricultural Mechanization,2014,35(6):76-79.
[6] 林加勇,刘继军,孟庆利,等.公猪舍夏季温度和流场数值CFD模拟及验证[J].农业工程学报,2016,32(23):207-212.Lin Jiayong,Liu Jijun,Meng Qingli,et al.Numerical CFD simulation and verification of summer indoor temperature and airflow field in boar building [J].Transactions of the Chinese Society of Agricultural Engineering,2016,32(23):207-212.
[7] Han J H,Kwon H J,Yoon J Y,et al.Analysis of the thermal environment in a mushroom house using sensible heat balance and 3-D computational fluid dynamics [J].Biosystems Engineering,2009,104(3):417-424.
[8] 吴飞青,胥芳,张立彬,等.基于多孔介质的玻璃温室加热环境数值模拟[J].农业机械学报,2011,42(2):180-185.Wu Feiqing,Xu Fang,Zhang Libin,et al.Numerical simulation on thermal environment of heated glass greenhouse[J].Transactions of the Chinese Society of Agricultural Machinery,2011,42(2):180-185.
[9] 罗进.利用信息熵计算评价指标权重原理及实例[J].武汉纺织大学学报,2014,27(6):86-89.Luo Jin.Principles and examples of using information entropy to calculate weight [J].Journal of Wuhan Textile University,2014,27(6):86-89.
[10] Zhang X,Wang H,Zou Z R,et al.CFD and weighted entropy based simulation and optimisation of chinese solar greenhouse temperature distribution [J].Biosystems Engineering,2016,142:12-26.
[11] 禚同友,丛建民.响应面法优化酶解玉米秸秆工艺研究[J].中国农机化学报,2017,38(3):93-99.Zhuo Tongyou,Cong Jianmin.Optimization of enzymatic hydrolysis technology for corn stalk by response surface method [J].Journal of Chinese Agricultural Mechanization,2017,38(3):93-99.
[12] 薛党勤.基于CFD的农用车辆冷却水泵正交优化分析研究[J].中国农机化学报,2016,37(9):135-139.Xue Dangqin.Analysis on orthogonal optimization of cooling pump in agricultural vehicle based on CFD [J].Journal of Chinese Agricultural Mechanization,2016,37(9):135-139.
[13] Ivakhnenko A G.The group method of data handling-a rival of the method of stochastic approximation [J].Soviet Automatic Control,1968,13:43-55.
[14] Wu J,Wang Y,Zhang X,et al.A novel state of health estimation method of Li-ion battery using group method of data handling [J].Journal of Power Sources,2016,327:457-464.
[15] Najafzadeh M,Barani G A.Comparison of group method of data handling based genetic programming and back propagation systems to predict scour depth around bridge piers [J].Scientia Iranica,2011,18(6):1207-1213.
[16] Atashrouz S,Pazuki G,Kakhki S S.A GMDH-type neural network for prediction of water activity in glycol and Poly(ethylene glycol) solutions [J].Journal of Molecular Liquids,2015,202(202):95-100.
[17] 刘艳阳,崔亮,张晔,等.基于COMSOL的马铃薯原料库置换通风系统仿真与分析[J].中国农机化学报,2018,39(10):65-70.Liu Yanyang,Cui Liang,Zhang Ye,et al.Simulation and analysis of displacement ventilation system for potato raw material storage based on COMSOL [J].Journal of Chinese Agricultural Mechanization,2018,39(10):65-70.
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