| 1. | instead, with an iterative approach, an initial guess for the solution of (6. 109) is used.
取而代之的是迭代的逼近法，并使用（6109）的解最初的估值。 |
| 2. | It does n ' t require good initial guess for convergence but approximately amount level
识别结果精度对初值的要求不高，只需给出大致的数量级。 |
| 3. | By taking these spatial points as initial guess , all exact real solutions withi n a certain range of variables are found using unrestraint optimization
以这些空间点为初始值，利用无约束优化，得到在一定值范围内的原方程组的全部精确实数解。 |
| 4. | Numerical results for two media with different properties show that the proposed initial guesses improve computational efficiency and reduce the influence of nonlinear solver on the time step as well
对两种不同性质的介质进行数值实验，结果表明，所设计的初值选取方法不仅大大提高了计算效率，而且能够降低非线性解法器对时间步长的影响。 |
| 5. | In this paper , taking the measured error sound velocity profile as the initial guess value , the sound beam travel times and beam angle recorded by the multi - beam system and the generalized linear inversion method are used to get a sound velocity profile close to the actual sound velocity profile , and the inversed sound velocity profiles have contributed to the reduction of sound velocity profile error
摘要以测得的误差声速剖面作为初始猜测值，利用多波束记录到的波束传播时间和波束角等信息，通过广义线性反演得到一个与实际声速剖面比较接近的声速剖面，这有助于减少声速剖面的误差。 |
| 6. | The method employs a recently developed direct optimization technique that uses a piecewise polynomial representation for the state and controls , thus converting the optimal control problem into a nonlinear programming problem . the method is remarkably robust to initial guesses , which is better than traditional method
这种方法利用了近些年来发展起来的直接优化技术，用分段多项式来表示整个轨道的状态和控制向量，将最优控制问题转化为非线性规划问题来研究。 |
| 7. | 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。 |
| 8. | Main results follows : ( 1 ) the computational result of this paper verifies ( though only in numerical sense ) the assumption about the structure and distribution of the multiple solutions of odd nonlinear equations [ 4 ] , and we can obtain the corresponding solution from any given initial guess [ 4 ] more solutions can be obtained by isem than by any other existed methods ( such as mpa , hla ) in some domains ( such as square , triangle and l domain )
主要结果如下： ( 1 )利用isem方法算得的数值结果初步证实了文[ 4 ]中关于奇非线性椭圆型方程多解的分布结构的猜想，从任一特定的初值出发，可以算得它所对应的解。在某些区域(正方形区域、三角形区域和上型区域)上算得了比现有的其他方法(山路型算法mpa和high - linking算法等)更多的解。 |
| 9. | Ga is less prone to converge to a local optimum even when the initial guess is far away from the exact solution . in recent years , a growing number of researchers in the ga community turn to the study of real - coded genetic algorithm ( rga ) for its simplicity and efficiency , and the reason that a chromosome can be directly represented by real number
然后引入全局优化的搜索方法?遗传算法，由于实数遗传算法直接用实数表示遗传个体，而微波成像算法就是要得出目标的形状函数，形状函数的系数既为待求的变量，具有连续搜索空间，因此本文直接采用实数遗传算法。 |
