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基于模糊决策树的温室温度调控
引用本文:马国兴,李雪非,冯慧敏,李永梅.基于模糊决策树的温室温度调控[J].安徽农业科学,2014(30):10443-10445,10486.
作者姓名:马国兴  李雪非  冯慧敏  李永梅
作者单位:邯郸市康源种植有限公司,河北邯郸057550;肥乡县职教中心,河北邯郸057550;河北农业大学理学院,河北保定,071001;河北大学数学与计算机学院,河北保定,071002;肥乡县职教中心,河北邯郸,057550
基金项目:邯郸市科学技术研究与发展计划项目
摘    要:现代化农业是以优质、高效为标志的,因而温室自动技术得到长足的发展.温度自动控制系统是温室技术中一个关键因素.模糊决策树是一种归纳学习算法,能够很好地逼近离散值函数,有较高的准确性且有很好的抗噪声特性.将模糊决策树引入温室的温度自动控制中,实现温度的自动控制,其产生的控制过程更易于理解,并且具有很好的抗噪声效果.仿真结果表明,基于模糊决策树的控制系统有较强的自适应能力与稳健性.

关 键 词:模糊决策树  稳健性  温度控制

Control Algorithm for Greenhouse Temperature Based on Fuzzy Decision Tree
Institution:MA Guo-xing, LI Xue-fei, FENG Hui-min et al ( 1. Handan Kangyuan Planting Co. Ltd, Handan, Hebei 057550 ; 2. Feixiang Vocationa/Education Center, Handan, Hebei 057550; 3. College of Science, Agricultural University of Hebei, Baoding, Hebei 071001 ; 4. College of Mathematics and Computer Science, Hebei University, Baoding, Hebei 071002)
Abstract:High quality and high efficiency are the characteristics of modem agricultural development. The greenhouse automatic control system has obtained great progress. Temperature automatic control is a key factor in greenhouse system. Fuzzy decision trees are a inductive learning algorithm, which can approximate well discrete valued function. It has more accurate and better robustness with respect to noise. The fuzzy deeision tree is introduced into temperature control to achieve automatic control. The result of fuzzy decision tree is more easily understood and more robust to noise. The simulation results show that temperature automatic control system based on fuzzy decision tree has better adaptive ability and robustness.
Keywords:Fuzzy decision tree  Robustness  Temperature control
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