摘要
讨论了利用粒子群优化(PSO)算法来训练BP神经网络的权值和阀值的原理,分析了三种GPS高程拟合实例,结果表明PSO-BP模型可以应用于GPS高程拟合中。
We discuss how to use particle swarm optimization （PSO） algorithm to train the BP neural network weights and threshold, and the specific implementation process of the both combination. Comparing with three GPS elevation fitting methods PSO-BP model has better precision and can be applied to the GPS elevation fitting.
出处
《测绘信息与工程》
2009年第6期18-20,共3页
Journal of Geomatics
关键词
粒子群优化
BP神经网络
高程拟合
particle swarm optimization algorithm
BP neural network
elevation fitting
