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中文摘要：
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。
英文摘要：
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.
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