新型工业化
新型工業化
신형공업화
New Industrialization Straregy
2012年
4期
8-15
,共8页
蚁群算法%BP神经网络%优化方法%交通流预测
蟻群算法%BP神經網絡%優化方法%交通流預測
의군산법%BP신경망락%우화방법%교통류예측
Ant colony algorithm%BP neural network%optimization method%traffic flow forecasting
BP 神经网络是人工神经网络中应用最广泛的一种多层前馈神经网络。针对它容易陷入局部极小值及隐层节点大多利用经验试凑来确定的缺点，本文提出了一种基于蚁群算法的BP神经网络结构及参数优化方法，利用蚁群算法的全局寻优能力克服BP神经网络存在的不足。最后，将该方法用于短时交通流预测，实验结果表明：利用蚁群算法优化神经网络是有效的，预测结果也有较高精度。
BP 神經網絡是人工神經網絡中應用最廣汎的一種多層前饋神經網絡。針對它容易陷入跼部極小值及隱層節點大多利用經驗試湊來確定的缺點，本文提齣瞭一種基于蟻群算法的BP神經網絡結構及參數優化方法，利用蟻群算法的全跼尋優能力剋服BP神經網絡存在的不足。最後，將該方法用于短時交通流預測，實驗結果錶明：利用蟻群算法優化神經網絡是有效的，預測結果也有較高精度。
BP 신경망락시인공신경망락중응용최엄범적일충다층전궤신경망락。침대타용역함입국부겁소치급은층절점대다이용경험시주래학정적결점，본문제출료일충기우의군산법적BP신경망락결구급삼수우화방법，이용의군산법적전국심우능력극복BP신경망락존재적불족。최후，장해방법용우단시교통류예측，실험결과표명：이용의군산법우화신경망락시유효적，예측결과야유교고정도。
BP neural network is the most widely used multilayer feedforward artificial neural networks, however,it is vulnerable to be trapped in local minimum and there is no systematic method to determine the number of hidden layer nodes thus usually done empirically. This paper introduces a method to optimize the structure and parameters of BP neural network which integrates ant colony algorithm with BP neural network to overcome shortcomings of traditional BP neural networks. The proposed method has been applied in short-term traffic flow forecasting. Simulation results demonstrate that the new BP neural network based on ant colony algorithm is more effective and can provide higher precision in traffic flow forecasting.
