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一维搜索

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In addition,the authors propose that for a multi peaked one dimensional search problem its optimum solution can be obtained by ordinary optimization methods only when the convexity or concavity of the objective function matches the step length determining the one dimensional search region and the method of finding the optimum step length factor.

另外 ,还提出了对于多峰一维搜索问题,只有当所求函数的凹凸性与确定一维搜索区问题的步长以及求解最优步长因子的方法匹配时,才能用一般方法得到搜索区间内的最优解

The system parameters are determined by optimizing an output-error cost function. To deal with the non-uniqueness of the fully parameterized state-space system, a projected gradient search algorithm is presented by restricting the update of the parameters to the tangent space to the manifold of observationally equivalent state-space systems. The sufficient condition to employ L-M algorithm for optimizing parameters is also introduced. The proposed hierarchical optimization identificationmethod includes two steps: First, the parameter search direction is determined by the proposed adaptive L-M projected gradient approach; Second, the optimum step size is computed according to a line search method.

通过极小化输出误差目标函数获得了系统参数估计;提出了正交梯度搜索方法用于解决系统参数的非唯一性问题,正交梯度搜索的本质是在输入-输出等价类相切平面的正交垂空间更新系统参数;给出了用 L-M 算法进行参数优化的充分条件;提出的系统参数递阶优化辨识方法包括两步:首先用给出的自适应 L-M 算子正交梯度方法确定参数优化方向;其次由一维搜索方法计算最佳步长。

Line search which is the optimization of single variable function is one of the methods for solving the problem of unconstrained nonlinear programming.

一维搜索又称线搜索,就是指单变量函数的最优化,是求解无约束非线性规划问题的基本方法之一。

The content of this course includes cost benefit analysis method, the basis of optimization theory, one dimension optimization,nonrestraint multi-dimension optimization theory, linear programming, nonlinear programming, dynamic programming, Monte Carlo Method.

课程内容包括工程系统决策分析内容和步骤,费用—效益分析方法及其应用,最优化方法基础,一维搜索方法,无约束的多维搜索方法,非线性规划算法及其应用,线性规划算法及其应用,动态规划及其应用,蒙特卡洛方法及其应用等。

First of all, on the base of the reduced gradient method of Wolfe, we added accurate one dimension searching method into it and gained a new algorithm (algorithm 1,2) for the nonlinear programming with linear equality constraints and quadratic programming problems, and proved convergence of algorithm, then, we use above algo...

首先本文在Wolfe既约梯度法的基础上,针对具有线性等式约束的非线性规划问题和二次规划问题,引入了精确的一维搜索,得到了带一维搜索的新算法(算法1、2),并给出了算法的收敛性证明。

According to the primary principles of the half division method and Newton method ,a new method called horizontal secant method was presented for one dimension search.

根据经典的一维搜索算法———对分法和Newton 切线法的基本原理,提出了一种新的一维搜索算法———水平割线法。

By combining the one dimensional search procedure in the determinate nonlinear programming problem with the stochastic approximation procedure, a new yield optimization algorithm is proposed and the rate of convergence is increased.

将确定性非线性规化问题求解的一维搜索过程与随机逼近搜索过程结合,提出了一种全新的合格率优化算法,进一步提高了合格率优化过程的收敛速度。

The ambiguity of DOA estimation due to ignorance of the function form of angular signal distribution is analyzed and the DOA estimation without ambiguity is given. 4. A method of DOA estimation of distributed sources is proposed by using the knowledge of the unimodal property of angular signal distribution and independence between different distributed sources.

利用角信号分布函数的共轭对称性,提出了基于噪声子空间的极小最小特征值一维搜索分布式目标DOA估计方法,和基于信号子空间的极大最大特征值一维搜索分布式目标DOA估计方法。

With the guide of non-linear program theory, by using interpolative steps and inexact line search, an improved conjugate gradient method was found, by which the training rate of BP networks increases by tens or hundreds of times. Moreover, the improved method is effective to solve non-linear equations for which Newton's method does not converge owing to the problems of the quadratic derivative and inverse matrix.

通过大量的数值模拟试验发现,在非线性规划理论的指导下采用间插步骤和不精确的一维搜索技术改进的共轭梯度法,是基于梯度和共轭方向的连续搜索算法中最有效的算法,这种算法使BP网络的训练速度提高几十到几百倍,使BP网络的实际应用效果大为改善;而且这种算法对于用牛顿法由于求二阶导数和求逆矩阵等问题难于收敛的非线性方程组的求解也是很有效的。

The estimation of additive and dominance effects through QTL analysis by onedimensional search while ignoring epistases showed similar accuracy to that by two-dimensional search by including epistases. Existence of epistases could decrease the precision for the estimation of additive and dominance effects. The estimation of genetic main effects would be biased if ignoring the interaction effects of QTL×environment . Joint analysis of multiple environments including QE interaction effects could increase the precision for the estimation of genetic main effects.

忽略上位性效应的一维搜索QTL分析对加性效应和显性效应的估计精度与包括上位性的两维搜索QTL分析对这两种效应的估计精度相差不大,上位性的存在可能会降低对这两种效应估计的精度;忽略QTL×环境互作效应会导致对遗传主效应的有偏估计,而包括QE互作效应的多环境联合分析能够提高对遗传主效应的估计精度。

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