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initial guess in Chinese

Pronunciation:
How to pronounce "initial guess""initial guess" in a sentence

Translationmobile phoneMobile

  • 初始猜測(cè)

Examples

  • 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。
  • It does n ' t require good initial guess for convergence but approximately amount level
    識(shí)別結(jié)果精度對(duì)初值的要求不高，只需給出大致的數(shù)量級(jí)。
  • By taking these spatial points as initial guess , all exact real solutions withi n a certain range of variables are found using unrestraint optimization
    以這些空間點(diǎn)為初始值，利用無約束優(yōu)化，得到在一定值范圍內(nèi)的原方程組的全部精確實(shí)數(shù)解。
  • 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
    對(duì)兩種不同性質(zhì)的介質(zhì)進(jìn)行數(shù)值實(shí)驗(yàn)，結(jié)果表明，所設(shè)計(jì)的初值選取方法不僅大大提高了計(jì)算效率，而且能夠降低非線性解法器對(duì)時(shí)間步長的影響。
  • 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
    摘要以測(cè)得的誤差聲速剖面作為初始猜測(cè)值，利用多波束記錄到的波束傳播時(shí)間和波束角等信息，通過廣義線性反演得到一個(gè)與實(shí)際聲速剖面比較接近的聲速剖面，這有助于減少聲速剖面的誤差。
  • 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
    這種方法利用了近些年來發(fā)展起來的直接優(yōu)化技術(shù)，用分段多項(xiàng)式來表示整個(gè)軌道的狀態(tài)和控制向量，將最優(yōu)控制問題轉(zhuǎn)化為非線性規(guī)劃問題來研究。
  • 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
    摘要結(jié)合復(fù)形法與粒子群算法的優(yōu)點(diǎn)，提出粒子群復(fù)形法，用于求解非線性方程組，以克服牛頓法初始點(diǎn)不易選擇的問題，同時(shí)克服復(fù)形法與粒子群算法由于易陷入局部極值而導(dǎo)致方程組的解的精度不夠的不足。
  • 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 )
    主要結(jié)果如下： ( 1 )利用isem方法算得的數(shù)值結(jié)果初步證實(shí)了文[ 4 ]中關(guān)于奇非線性橢圓型方程多解的分布結(jié)構(gòu)的猜想，從任一特定的初值出發(fā)，可以算得它所對(duì)應(yīng)的解。在某些區(qū)域(正方形區(qū)域、三角形區(qū)域和上型區(qū)域)上算得了比現(xiàn)有的其他方法(山路型算法mpa和high - linking算法等)更多的解。
  • 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
    然后引入全局優(yōu)化的搜索方法?遺傳算法，由于實(shí)數(shù)遺傳算法直接用實(shí)數(shù)表示遺傳個(gè)體，而微波成像算法就是要得出目標(biāo)的形狀函數(shù)，形狀函數(shù)的系數(shù)既為待求的變量，具有連續(xù)搜索空間，因此本文直接采用實(shí)數(shù)遺傳算法。
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