中文摘要：

基于不确定度理论,建立参数有界约束下的平差模型。为克服不等式约束模型单边约束的缺陷,从最小二乘出发,将问题转化为附有箱型约束的二次规划问题,提出一种求解参数最优估值的新算法,并给出参数估计的统计性质。数值实验表明,新算法简单、可行,具有较快的收敛速度,并能够在一定程度上减少部分数值的部分不确定性。

英文摘要：

Based on uncertainty theory, this paper establishes the parameter-bounded adjustment model and o- vercomes the defects of inequality-constrained adjustment. Due to the least squares, the problem is converted into a quadratic programming problem with box constraints, proposes a new algorithm to calculate the optimal values of parameters, and gives the statistical properties of parameter estimation. Numerical experiments vali- date that the new algorithm is simple, feasible, has a faster convergence speed, and show that the algorithm can reduce some numerical uncertainty.