基于改进遗传算法的温湿度模糊神经网络控制器  

New temperature and humidity fuzzy neural network controller based on improved genetic algorithm

作　　者：李秀梅[1] 赵春江[1] 乔晓军[1] 刘华毅[2] 

机构地区：[1]国家农业信息化工程技术研究中心,北京100089 [2]大连理工大学,大连116024

出　　处：《农业工程学报》2004年第1期259-262,共4页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家863计划(2001AA247022);北京市工厂化高效农业项目(H020720030530);北京市农业技术试验示范项目(20012014)

摘　　要：为了创造适合作物生长的环境,针对温室系统的特点,该文提出了一种基于改进遗传算法的模糊神经网络控制器,利用改进遗传算法训练模糊神经网络模型,采用此模糊神经网络控制器控制温室系统,由数值实验可以看到采用此控制器的温室系统具有响应速度快、过程平稳、编程简单的特点。The greenhouse is a complex system. There is strong coupling relationship among its environmental factors in side greenhouse. So it's difficult to get satisfying effect by using conventional control methods. Based on the characteristics of the greenhouse, a new fuzzy neural network controller (FNNC) was proposed to create a proper condition for crop growth. The improved genetic algorithm was used to train the architecture of the fuzzy neural network controller, which was adopted in the greenhouse. Numerical experiment results showed that the greenhouse equipped with this fuzzy neural network controller had such features as responding quickly, smooth transition and programming simply.

关 键 词：模糊神经网络控制器 改进遗传算法 温室 

分 类 号：S625.51[农业科学—园艺学]