关键词: 人工内分泌网络模型, 渗透系数, 孔隙度, 水文地质, 含水层

Abstract:

Although various methods can be used to determine hydraulic conductivity of aquifer, each method has faults that limit application, such as the results mainly dependent on the geometry and hydraulic boundaries of the streambed; The accurate value of coefficient C is difficult to obtain. The authors proposed a new method-Artificial Endocrine Network Model (AENM), and described its algorithm principle. In order to verify the validity of AENM, the traditional empirical formulas and AENM were applied in alluvial-pluvial fan front in North China Plain (NCP) to calculate hydraulic conductivity according to grain-size distribution and porosity. The results indicate that the Beyer formula was less accuracywith a relative error of 0.078-1.342, as to the  the Slichter method, the prediction accuracy rate was increased, but the forecasting error of extreme value was still larger with a relative error of 0.046-0.643; The prediction accuracy of AENM was higher, the relative error of 0.006-0.420. The AENM method has several advantageous over traditional methods which has not only higher calculation precision and stronger versatilitybut also could directly estimate vertical hydraulic conductivity without data transformation too long sentence to be revised. Therefore, the AENM method could be successfully used to study the hydrogeology parameter.

Key words: artificial endocrine network model, hydraulic conductivity, porosity, hydrogeology, aquifer