人民黄河
人民黃河
인민황하
Yellow River
2014年
1期
30-32
,共3页
神经网络%人工鱼群算法%封河日期%开河日期%宁蒙河段%黄河
神經網絡%人工魚群算法%封河日期%開河日期%寧矇河段%黃河
신경망락%인공어군산법%봉하일기%개하일기%저몽하단%황하
neural network%artificial fish swarm algorithm%freeze-up date%break-up date%Ningxia-Inner Mongolia section%Yellow River
在分析凌汛成因的基础上选取合适的预报因子，针对BP神经网络收敛速度慢、易陷入局部极小值的缺点，利用改进的人工鱼群算法训练BP神经网络，以黄河宁蒙河段封开河日期数据进行建模，给出了人工鱼群算法训练神经网络的基本原理和步骤，并对人工鱼群算法神经网络模型、遗传算法神经网络模型、粒子群神经网络模型的预测结果进行了对比分析。结果表明：人工鱼群算法神经网络模型对黄河内蒙古段凌汛期的封开河日期预测比较准确，预测结果优于遗传算法神经网络模型和粒子群神经网络模型。
在分析凌汛成因的基礎上選取閤適的預報因子，針對BP神經網絡收斂速度慢、易陷入跼部極小值的缺點，利用改進的人工魚群算法訓練BP神經網絡，以黃河寧矇河段封開河日期數據進行建模，給齣瞭人工魚群算法訓練神經網絡的基本原理和步驟，併對人工魚群算法神經網絡模型、遺傳算法神經網絡模型、粒子群神經網絡模型的預測結果進行瞭對比分析。結果錶明：人工魚群算法神經網絡模型對黃河內矇古段凌汛期的封開河日期預測比較準確，預測結果優于遺傳算法神經網絡模型和粒子群神經網絡模型。
재분석릉신성인적기출상선취합괄적예보인자，침대BP신경망락수렴속도만、역함입국부겁소치적결점，이용개진적인공어군산법훈련BP신경망락，이황하저몽하단봉개하일기수거진행건모，급출료인공어군산법훈련신경망락적기본원리화보취，병대인공어군산법신경망락모형、유전산법신경망락모형、입자군신경망락모형적예측결과진행료대비분석。결과표명：인공어군산법신경망락모형대황하내몽고단릉신기적봉개하일기예측비교준학，예측결과우우유전산법신경망락모형화입자군신경망락모형。
Based on the analysis on the factors affecting the formation of ice-jam flood,the most important factors for forecasting were selected. Ac-cording to weak points of slow convergence and being apt to local minimum about BP neural network,adopting artificial fish-swarm algorithm was suggested to train the artificial neural network. According to the freeze-up and break-up date of Ningxia-Inner Mongolia section of the Yellow River, neural networks had been trained by adopting AFSA to build an AFSA-NN,which was realized by MATLAB 7. 0 and employed to forecast ice flood. The case study shows that this algorithm forecast is correct for freeze-up and break-up date in the ice flood season in Inner Mongolia reach of the Yellow River. The forecast result is better than GA-BP and PSO-BP neural network.
