摘要
将人工神经网络的理论与方法应用到表层岩溶带地下水动态预报中,从不同角度建立了2个预报BP网络模型,A模型刻画水位与降雨量、蒸发量和泉流量之间的关系,相对误差为±2%;B模型刻画水位自身的变化规律,相对误差为±5%,均可用于预报水位.A,B模型可为表层岩溶水研究及开发利用提供依据.
The principle and the method of artificial neural network have been applied to the prediction of variation of groundwater levels in epikarst zone. Two prediction BP network models,i, e. A and B,have been built from different points of view. Model A depicts the relations between water level and the precipitation,evaporation and spring flux,and the relative errors of its forecasting results are less than 2 percent. Model B depicts the variation regularity of water level itself,and the relative errors are less than 5 percent. Two models can be both used to predict the water levels prcdiction,which can provide an evidence for the development and utilization of water in epikarst zone,and water level datum for research on epikarst zone.
出处
《广西师范大学学报（自然科学版）》
CAS
北大核心
2005年第4期99-102,共4页
Journal of Guangxi Normal University:Natural Science Edition
基金
国家自然科学基金资助项目(40272068)
国土资源部攻关项目(20010303)
国家科技攻关项目(2002BA901A13)
