基于神经网络的专家系统在温室控制中的应用  

The Application of Greenhouse Control Based on Neural-network Expert System

作　　者：张洪波[1] 陈平[1] 刘学[1] 余志强[1] 

机构地区：[1]中国电子科技集团公司第三十四研究所,广西桂林541004

出　　处：《成都信息工程学院学报》2010年第3期260-263,共4页Journal of Chengdu University of Information Technology

摘　　要：为了实现温室控制,针对温室环境的多输入、多输出、非线性和难以建立数学模型等特点,提出一种基于BP神经网络的专家系统并用于温室控制。该方法将传感器采集的温度、湿度等信息输入到神经网络专家系统,在获得决策结果的同时通知控制部分执行相应的决策。这种方法不仅解决了传统专家系统知识获取的瓶颈问题、推理能力差、智能化低的缺点,而且克服了神经网络不具有解释功能的问题。总之,成功实现了神经网络和专家系统功能上的互补,较好的用于温室控制。In order to implement greenhouse control, in accordance with greenhouse environment, which has multipleinput, multiple-output, non-linear, and difficult to establish mathematical models, an expert system based on Back- Propagation neural network has been proposed and used which achieve from sensors are input in the expert system. in greenhouse control. Data as temperature or humidity When we receive the decision, the system also informs the control block to react. The method not only solves the drawbacks of conventional expert system such as knowledge acquiring bottleneck, poor capability in reasoning and lower intelligent level, but also overcomes shortcomings that the neural network doesn＇t have interpreting function. In conclusion, the method which succeeds integrating merits of neural network and expert system can be used in greenhouse control.

关 键 词：BP神经网络 专家系统 温室控制 传感器 决策 

分 类 号：TP393.09[自动化与计算机技术—计算机应用技术]