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温室小气候建模方法研究现状与展望
引用本文:胥芳,余岚岚,陈教料,吴海洪.温室小气候建模方法研究现状与展望[J].农机化研究,2007(11):44-47,50.
作者姓名:胥芳  余岚岚  陈教料  吴海洪
作者单位:浙江工业大学,机械制造及自动化教育部重点实验室,浙江,杭州,310032
摘    要:综述了温室小气候模型的发展现状,包括依据能量和物质平衡的物理建模、线性和非线性的系统辨识建模,如递归最小二乘算法、神经网络等.并分别采用物理建模和神经网络系统辨识方法,通过实验对温室小气候进行建模与仿真.同时,指出了这些方法存在的一些局限性,最后就温室小气候杂交建模方法的发展趋势进行了展望.

关 键 词:园艺学  温室小气候  理论研究  物理模型  系统辨识  杂交模型  温室小气候  建模方法  研究  现状  Microclimate  Greenhouse  Modeling  Methods  趋势  法的发展  杂交  存在  建模与仿真  实验  辨识方法  网络系统  神经网络  算法  最小  递归  系统辨识建模
文章编号:1003-188X(2007)11-0044-04
收稿时间:2007-01-26
修稿时间:2007-01-26

The Actuality and Research Situation on the Modeling Methods of the Greenhouse Microclimate
XU Fang,YU Lan-lan,CHEN Jiao-liao,WU Hai-hong.The Actuality and Research Situation on the Modeling Methods of the Greenhouse Microclimate[J].Journal of Agricultural Mechanization Research,2007(11):44-47,50.
Authors:XU Fang  YU Lan-lan  CHEN Jiao-liao  WU Hai-hong
Institution:The MOE Key Laboratory of Mechanical Manufacture and Automation, Zhejiang University of Technology, Hangzhou 310032, China
Abstract:The development of the greenhouse microclimate model is summarized. These models could be based on energy and mass flows equations, derived by using a system identification approach using linear and non-linear techniques, such as the recursive least squares algorithms, neural networks to tune the parametric models. Experiments are used to emulating the greenhouse microclimate based on energy and mass flows equations and neural networks .And their drawbacks are pointed out. The development tendency of greenhouse microclimate model is expected.
Keywords:gardening  greenhouse microclimate  theoretical research  physical model  system identification  hybrid model
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