摘要
高速公路交通量预测对于高速公路建设和管理具有重要的指导作用,针对传统预测方法准确性低、预测时间长等问题,提出了将BP神经网络和遗传算法有机结合起来的遗传—神经网络预测模型,并且在实现过程中通过对两种算法的改进,进一步提高预测的效率和准确性,最终通过实验数据验证了该算法具有优良性能。
The traffic prediction has an important instructing effect on the highway construction and organization. Traditional prediction method has some problems,such as low accuracy and effficiency,so this paper presents a model based on the combination of genetic algorithm and artificial neural network,further more,by improving these two methods in the process of implementation,further increases the accuracy and efficiency.At last,some experiments are made to prove its fine performance.
出处
《计算机工程与应用》
CSCD
北大核心
2006年第4期226-228,共3页
Computer Engineering and Applications
关键词
遗传算法
人工神经网络
适应度
genetic algorithms,Artificial Neural Network,fitness