Research on GPS elevation fitting method for linear engineering

Aiming at the characteristics that mathematical models are only applicable to specific terrain and neural network models are easy to fall into local optimal solution, an optimal weighting algorithm is proposed. Two mathematical models and two neural network models are used to fit the GPS elevation of linear engineering respectively, and a single algorithm with good fitting effect of each model is combined into an optimal weighting algorithm. The results show that the polynomial fitting algorithm is superior to the multifaceted function method, and the genetic simulated annealing algorithm optimized BP neural network algorithm (GSA-BP) is better than other algorithms, which is the best single algorithm. The precision of the weighted algorithm is 17.7% and 10.0% higher than that of the single member algorithm, respectively, and can basically meet the requirements of the fourth grade leveling, which is feasible in GPS elevation fitting of linear engineering.