摘要
根据人工神经网络处理大规模非线性动力系统、遗传算法具有较好的寻优能力的特点,将二者有机的结合起来,提出了基于遗传算法改进的洪水预报模型,并将其应用于四川省达州市州河流域的水文预报。实验结果表明,本模型能够减少训练次数,提高预报精度,能更好的对洪水进行预报。
Based on artificial neural network can deal large-scale nonlinear dynamic system, genetic algorithm has good optimization ability, combined the two with their full advantages, proposed the flood forecast model that based on improved genetic algorithm, and applied to hydrological forecast to zhou river basin, Dazhou City, Sichuan Province. Experimental results show that the model can decrease the times of training and improve the prediction precision, better for flood forecast.
出处
《电子设计工程》
2014年第2期10-12,15,共4页
Electronic Design Engineering
基金
四川省教育厅2011年面上项目(11ZB139)
达州市2011年科技攻关项目(JCY1117)
关键词
神经网络
遗传算法
洪水预报
模型
neural network
genetic algorithm
flood forecasting
model
