Water Temperature Forecast in Winter Using ANFIS in the Yellow River
The Inner Mongolia reach of the Yellow River lies on the northern part of the Yellow River Basin.In this reach of the river,looking like a reversed U,is easy for ice disaster to appear,such as flooding in the winter months.There is essential to timely and accurately forecast the ice conditions for protecting the urban and rural areas along the basin from being struck by possible ice-flooding disasters.However,in order to conduct ice condition forecasts,the freeze-up water temperature forecast in winter should be conducted at the first place.With its hybrid learning scheme,adaptive-network-based fuzzy inference system (ANFIS),constructed under the framework of the neural networks and fuzzy models,and the latter possess certain advantages over the former two,is convenient for modelling the nonlinear multivariable process; for instance,in the case of modelling the hydrological information variety.Consequently,ANFIS is applied to the freeze-up water temperature forecast in Inner Mongolia reach of the Yellow River including 4 hydrometric stations,i.e the Shizuishan Station,Bayangaole Station,Shanhuhekou Station,and Toudaoguai Station.And the forecast results of water temperature are compared with the measured records in these four hydrometric stations.Through such comparisons,it was discovered that the water temperature forecast results approximately agree with those of the field records.The ANFIS model is used for simulating the freeze-up water temperature forecast process in winter,and satisfactory results have been obtained.
ANFIS ice condition forecast freeze-up water temperature the Yellow River
Wang Tao Yang Kailin Guo Xinlei Fu Hui Guo Yongxin
China Institute of Water Resources and Hydropower Research, Beijing, 100038, China
国际会议
The 5th International Yellow River Forum (第五届黄河国际论坛)
郑州
英文
182-190
2012-09-24（万方平台首次上网日期，不代表论文的发表时间）