Abstract：In order to improve the calculation efficiency of adjustment models with uncertainty based on F-norm, a directly iterative algorithm is developed. The algorithm does not use singular value decomposition (SVD), is simple in the concept, and is easy to program. Another algorithm of SVD-equations is also given when the iterative algorithm is divergent. The results of the binary linear fitting and AR model in settlement observation illustrate that the two proposed algorithms could be practiced and are equivalent to the algorithm of SVD-iteration.The directly iterative algorithm is more suitable when the iterative algorithm is convergence, which has faster convergence rate and higher calculation efficiency. Moreover, the algorithm of SVD-equations can be used when the iterative algorithm is divergent.
