基于遗传算法优化的神经网络研究及应用

Research and Application of Neural Network Based on Genetic Algorithm Optimization

随着车辆的不断增多,城市的交通问题成为一个重要的研究课题。智能交通要求能够根据一些历史数据及时对交通量进行预测,以便决策者对路段进行控制,使得道路交通达到一种理想的控制效果。计算机技术的快速发展,使得人工智能在这个研究领域占有其独有的地位,也成为近年来计算机领域中研究的一个重点。在神经网络的实际应用中,均是采用BP神经网络或者改进模型。针对神经网络存在的问题,需要一种好的算法对神经网络进行优化,提高网络的整体性能。遗传算法在系统控制、结果优化等诸多应用领域方面都有十分成功的应用。

with the increasing number of vehicles, the traffic problem of the city has become an important research topic. Intelligent traffic demand can predict traffic volume timely according to some historical data, so that decision-makers can control the road sections, so that road traffic can achieve an ideal control effect. With the rapid development of computer technology, artificial intelligence occupies a unique position in this research field, and has also become a research focus in computer field in recent years.In the practical application of neural network, the BP neural network or the improved model are used. In order to solve the problem of neural network, a good algorithm is needed to optimize the neural network to improve the overall performance of the network. Genetic algorithms have been successfully applied in many fields such as system control, result optimization and so on.