摘要
基于人工神经网络技术 ,建立了地下水二维非稳定流数学模型的参数识别模型 ,用地下水长观孔水位降深资料识别模型参数。通过实例计算分析 ,结果表明此法适用于处理复杂条件下模型参数识别问题 ,且结果稳定可靠。
Based on artificial neural network theory, a parameter identification model for 2 D mathematical model for groundwater unsteady flow is established. Model parameters can be determined based on investigated data with groundwater observation wells. The calculated results shows that the method is suitable to model parameter identification under complicated conditions, and is good in stability and adaptability.
出处
《灌溉排水》
CSCD
北大核心
2002年第3期36-38,49,共4页
Irrigation and Drainage
基金
河南省科技攻关计划项目 (0 12 42 0 0 10 9)
