摘要
以重庆市巴南区东温泉泉域为研究对象,对东温泉泉域年内及年际流量变化特征及其影响因素进行了分析,研究发现,东温泉泉域流量动态不稳定,主要影响因素是降雨量和人工开采量;并利用人工神经网络BP算法,通过MATLAB软件的人机交互界面、对泉流量、开采量和降雨量的系列数据进行了网络训练,发现动态预测模型预报的泉流量与实际基本吻合,说明该模型拟合和预报能力较好,精度较高,可用于同类型地区的地下水开采量的预测.
This paper takes East Spa of Chongqing as the study object. First, the dynamic change in the spring area of the spa is investigated and its influencing factors are studied. Then, the series data of its spring flow, yield and rainfall are trained with the ANN BP algorithm, and a prediction model for the spring flow dynamics is established. Finally, the model is tested and analyzed. The results show that this model can predict the spring discharge of East Spring Basin with satisfactory accuracy and is recommended for application in the prediction of groundwater resources in similar regions.
出处
《西南大学学报（自然科学版）》
CAS
CSCD
北大核心
2013年第6期142-148,共7页
Journal of Southwest University(Natural Science Edition)
基金
国家自然科学基金资助项目(41103068
41072192)
2011年度重庆市国土房管局科技计划资助项目
中央高校基本科研业务费专项资金资助项目(XDJK2012B005)
岩溶动力学重点实验室开放基金资助项目(KDL2012-08)
关键词
人工神经网络
地下水动态模型
东温泉
重庆市巴南区
artificial neural network （ANN）
Chongqing groundwater dynamic model
East Spa
Banan District
