GPS Height Fitting Based on BP Neural Network Combination Model
In order to improve the height fitting accuracy of BP (back propagation) neural network, this paper introduces simulated annealing (SA) algorithm based on BP neural network height fitting method to form a new SA-BP height fitting method. The combina-tion method gives full play to the advantage of SA algorithm in global optimization, and optimizes the initial value, weight and thresh-old of BP neural network fitting method. The combined height fitting method proposed in this paper is applied to the measured GPS benchmark elevation data in flat survey area and complex survey area. The experimental results show that the combined height fitting method proposed in this paper can effectively fit the experimental elevation data, and the fitting accuracy is higher than the traditional surface fitting method and BP neural network method, which verifies the reliability, superiority and good adaptability to different ter-rain conditions of the method proposed in this paper.
万方数据
维普
