方程组的解 meaning in English
solution of equations
Examples
- In this method , the parameters to be estimated are divided into two sections , the number of equation dimension is reduced by half , so the solution of equation is simplified , and the working efficiency is greatly raised
在这种解算方法中，由于将待估参数分成了两部分，使原本庞大的高维方程组的解算得以简化，把待求参数的维数减半，大大提高了工作效率。 - The referenced functions of those solutions for those important problems in system planning , such as investment estimation of software and hardware , service optimization , system updating , maintaining project designing , etc , were explained
根据测试数据得到方程组的解，研究表明解在系统规划过程中对软、硬件投资估算、服务优化、系统升级、维护方案设计等方面有很好的参考作用。 - The solution s characteristic of the elliptic type eq uat ion and the system of elliptic type equations with first order are discussed by using the methods of several complex analysis . a series new extended results of t he soutions for the system of elliptic type equations are obtained
将一阶椭圆型实方程和椭圆型实方程组转化为椭圆型复方程和椭圆型复方程组,借助于多元复分析的方法,研究了一阶椭圆型方程和椭圆型方程组的解的特征,得到了有关一阶椭圆型方程组解的一系列新的延拓结果 - A complex particle swarm optimization ( cpso ) algorithm , which combines the advantages of method of complex ( mc ) and particle swarm optimization ( pso ) , is put forward to solve systems of nonlinear equations , and it can be used to overcome the difficulty in selecting good initial guess for newton ' s method and the inaccuracy of mc and pso due to being easily trapped into local minima for solving systems of nonlinear equations
摘要结合复形法与粒子群算法的优点，提出粒子群复形法，用于求解非线性方程组，以克服牛顿法初始点不易选择的问题，同时克服复形法与粒子群算法由于易陷入局部极值而导致方程组的解的精度不够的不足。 - Recently , yamashita and fukushima [ 4 ] show that the sequence produced by the levenberg - marquardt method converges quadraticlly to the solution set of the equations , if the parameter is chosen as the quadratic norm of the function and under the weaker condition than the nonsingularity that the function provides a local error bound near the solution . however , the quadratic term has some unsatisfactory properties
最近yamashita & fukushima [ 4 ]提出，在弱于非奇异性条件的局部误差界条件下，如果选取的迭代参数为当前迭代点处函数值模的平方，则levenberg - marquardt方法产生的迭代点列二阶收敛于方程组的解集。