CAJ | 학술논문

本文将神经网络用于松花江干流河道汇流计算和河道洪峰水位的预报.对各种转移函数的效果进行了比较,线性函数和双正切函的精度较好超过传统的马斯京根法,其中线性转移函数最好,说明对于大江大河线性转移函数最好.由上游断面洪峰水位预报下游断面洪峰水位也取得了良好的效果.
본문장신경망락용우송화강간류하도회류계산화하도홍봉수위적예보.대각충전이함수적효과진행료비교,선성함수화쌍정절함적정도교호초과전통적마사경근법,기중선성전이함수최호,설명대우대강대하선성전이함수최호.유상유단면홍봉수위예보하유단면홍봉수위야취득료량호적효과.
The application of BP neural network in channel muting and flood peak stage predicting in the Songhuajiang River Basin was introduced,what this study focused on was the effect of different activation function and the comparing with tradition hydrological models.In the channel muting results,all the activation functions are perfect.among which results from hyperbolic function and linear function are better than the Muskingum model,the result of linear function is the best.In the flood peak stage prediction,good results were obtained from sigmoid and linear function.