遗传算法改进的BP神经网络在GPS高程拟合中的应用  

Application of BP neural network based on GA to GPS height fitting

作　　者：李和旺[1] 任超[2,3] 

机构地区：[1]贺州学院数学系,广西贺州542800 [2]桂林理工大学测绘地理信息学院,广西桂林541004 [3]广西空间信息与测绘重点实验室,广西桂林541004

出　　处：《工程勘察》2012年第12期55-57,74,共4页Geotechnical Investigation & Surveying

基　　金：国家自然科学基金项目(41071294);广西自然科学基金资助项目(编号:桂科自0640178);广西科学基金资助项目(编号:桂科基0991023)

摘　　要：针对BP神经网络收敛速度慢和易于陷入局部极小值的问题,采用将遗传算法全局寻优和BP神经网络局部寻优相结合的方法,优化神经网络各层之间的连接权和阈值,提高了BP神经网络的计算精度、收敛速度和泛化能力。本文论述了遗传算法的基本思想、实现过程,并对高程拟合算例进行训练检验,实验结果表明,遗传算法改进的BP神经网络进行GPS高程拟合是可行的,能够有效地提高BP神经网络的拟合精度。The problems of slow convergence speed and being prone to converge to local minimum are solved by using the method of combining the characteristics of global optimization of GA （Genetic Algorithm） with local optimization of BP neural network. The method optimized the link weight and the threshold of the neural network layers, improved accuracy, convergence speed and generalization ability of the calculation. This paper discusses the basic idea of genetic algorithms, the implementation process, training examples of height fitting. The results of experiments show that BP neural network base on GA is feasible and capable to improve the fitting accuracy effectively in GPS height fitting.

关 键 词：GPS BP神经网络 遗传算法 高程拟合 

分 类 号：P228.4[天文地球—大地测量学与测量工程]