Ice Breakup Date Forecast with Hybrid Artificial Neural Networks

被引：6

作者：

Hu, Jinbao ^{[1
]}

Liu, Ling ^{[1
]}

Huang, Zhengping ^{[1
]}

You, Yang ^{[1
]}

Ra, Suqiu ^{[2
]}

机构：

[1] Hohai Univ, State Key Lab Hydrol Water Resources & Hydraul En, Nanjing 210098, Peoples R China

[2] Hydrol Bur Yellow River Conservancy Commiss, Zhengzhou 450000, Peoples R China

来源：

ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 2, PROCEEDINGS | 2008年

关键词：

D O I：

10.1109/ICNC.2008.169

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A hybrid artificial. neural network model combining particle swarm optimization (PSO) and back propagation (BP) was used for ice breakup date forecast in the top reach of the Yellow River, China. A comparison of PSO-BP model to other statistical models was also conducted to evaluate the performance of the PSO-BP model. The forecast results indicate a satisfactory performance in the ice breakup date forecast with the PSO-BP model. The study concludes that the hybrid artificial neural network model combining PSO and BP has the high practicability and good accuracy for describing complex nonlinear ice breakup processes.

引用

页码：414 / +

页数：2

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