polynomial complexity meaning in Chinese
多项式复杂性
Examples
- Because the most scheduling problem is np hard , it is impossible to find out common algorithm with polynomial complexity
由于调度问题大多数都是具有np难度的组合优化问题，寻找具有多项式复杂性的优化方法几乎是不可能的。 - An infeasible path - following algorithm is constructed , and its polynomial complexity is analyzed . numerical tests show the self - adjusting effect of the parameters
基于这组方程，文中建立了一个求解线性互补的不可行内点算法，并分析了它的多项式复杂度。 - For the total tardiness scheduling with precedence constraints , an approximation algorithm with polynomial complexity was presented by transplanting the backward - shift algorithm of the case without precedence constraints
摘要把工件之间不带前后约束的延误排序的后移算法移植到带有前后约束的情况，提出一个多项式时间的近似算法。 - By making algebraically equivalent transformation for the standard centering equation xs = e , we obtain a new system of perturbed k - k - t equations and , for specific power transformation , recover the newton equations that are recently used by j . m . peng et al to show a lower polynomial complexity bound for large - update algorithm
前述的两种方法是针对扰动k一k一t系统进行的，而本文的另一种方法是采用ncp函数，直接将标准线性规划k一k一t条件化为一个不含内点约束的等价方程组，以此改造标准摄动方程组。 - This algorithm improves confidence in se by estimating parameters and states at the same time . simulation results on test power systems which range in size from 4 to 118 buses , have shown the virtues as follows : getting unbiased estimation without detecting and identifying bad data in measurements ; solving state and parameter estimation for power system with good convergence and excellent robust property ; increasing the numbers of iterations a little bit with the test systems expanded ; estimating many transformer taps simultaneously and remaining the main state estimation ; keeping the estimated relative error within + 0 . 1 % and processing efficiently equality constraints and ill condition with polynomial complexity
对ieee ? 4 118节点系统和广西主网进行的仿真结果表明： l1范数估计具有不良数据拒绝特性，当量测量中存在不良数据时，该算法在不经检测和辨识不良数据情况下仍是无偏估计，具有良好收敛性，所需迭代次数随着问题规模扩大而增长极小；能够同时估计多个变压器抽头，并保持状态估计主体；在满足可观测性条件下，估计的相对误差保证在0 . 1以内；能够有效处理等式约束和病态条件，并具有多项式时间性。