摘要
采用神经网络和遗传算法,对温室栽培番茄生长过程中主要器官——茎的生长过程进行了建模.温室番茄的生长过程具有控制变量多、生长过程复杂等特点.采用基于径向基函数(RBF)神经网络的辨识方法建立了温室栽培番茄生长的模型,以温室中番茄的实测数据为训练和预测样本,采用遗传算法进行训练.仿真结果表明,该方法较其他方法更适合于温室番茄生长过程的建模.
The modeling of the growing status of the cauline of tomato in growing process is discussed, by using NN and genetic algorithm. The model of the growing process of tomato is constructed based on RBF neural network. The real data of the tomato planted in greenhouse are used as the sample data and the genetic algorithm is used for getting the parameters. Simulation results show that the model has better performance than those based on other method.
出处
《控制与决策》
EI
CSCD
北大核心
2005年第6期682-685,共4页
Control and Decision
基金
"十五"国家重点科技攻关项目(2001BA503B01).
关键词
径向基函数网络
遗传算法
建模
Genetic algorithms
Greenhouses
Neural networks
Radial basis function networks