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一维搜索

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Through the suitable selection of difference quotient and correction of the one-dimension inaccuracy linear searching,scope of the improved method is extended.

从应用角度出发,首先,将约束变尺度法改进为一般约束条件,通过适当选择差商形式和对一维不精确线性搜索方法的修正,扩大了该方法的适用范围。

In the layout analysis, we chose a bottom-up algorithm based on nearest neighbor connect-strength and line confidence to segment the image area, table area and text area; In the printed Chinese character recognition module, we calculate the degree of incorporative difference to match the character, also define a refusal class which could orientate the mathematical expression automatically; Put the expression into the formula processing module, then we chose the character segmentation method based on connectivity and the template match method to recognize the character in the mathematical expression and at last we used the structure analysis based on the character to transform the two dimension formula into one dimension Word EQ expression.

在版面分析中,采用基于最近邻连接强度和行列可信度的自底向上的版面分析算法,分割出图像区域、表格区域和文本区域;在汉字识别模块中,采用回溯切分方法切分出字符段,计算合并差异度与特征字典比较,通过引入汉字的拒识类,从而实现了公式的定位;将定位后的数学公式送入公式识别器,在公式识别器中采用基于连通域搜索的字符分割方法和模板匹配方法对字符识别,对于识别出的字符,再采用基于特征字符的结构分析方法,从而将二维的数学公式转化为一维的Word EO域语句。

Instead of multidimensional nonlinear search or iterative computation, the algorithm just uses a one-dimensional search and can reduce the computation burden.

算法的波达方向估计只需一维谱峰搜索,避免了通常多参数联合估计的多维非线性搜索及迭代运算,可明显减小算法运算量。

With Hilbert space filling curve and latent semantic index, MLSQ maps similar data objects in high dimension semantic space into an adjacent range in one dimensional value space, and considers every data object sequence number in one dimensional space as a key. MLSQ distributes the keys to adjacent nodes of structured P2P systems. By embedding the process of searching data points of HSFC into the nodes of structured P2P networks and using the data search mechanism of networks, MLSQ can facilitate to search the data objects in accordance with query requirements.

该方法利用Hilbert空间填充曲线和潜在语义索引,将高维语义空间中相似的数据对象映射到一维数值空间中的邻近区域中,并以每个数据对象在一维数值空间中的序号作为键,将数据对象的索引分布到有组织P2P网络邻近的结点上,通过将HSFC中数据点的查找过程嵌入到有组织P2P网络的结点上,再利用网络的数据查找机制,MLSQ可方便地搜索到符合查询要求的数据对象。

In this paper, genetic algorithm is used for the route optimizing of SLMM. The path points and threats position are denoted in the form of polar coordinates, which can shorten the gene code length, speed up the execution of genetic search for fast path generation.

采用遗传算法进行自航水雷航路优化,算法利用极坐标描述威胁位置和航路点,将航路编码由二维缩减至一维,降低了搜索空间,提高了优化效率。

Thereinto, quadratic interpolation is uesed in undimensional search, and Powell arithmetic is used to solve unconstrained minimziation.

其中,利用二次插值法进行一维搜索,选用Powell算法进行无约束极小化求解。

This paper presents a multigrid parallel algorithm of one dimensional virtual boundary ransack forecast, and discusses its convergence.

对网格方程组作多重网格区域分裂并行计算,虚拟边界预报提出一维搜索算法,并讨论相应的收敛性;通过 GS迭代的性质,构造区间压缩算法,证明了其收敛性。

Numerical simulations show that this self-adjusting algorithm is more flexible and effective than other existing algorithms, and more ideal results can be gained in a much shorter time.

数值模拟结果表明,自调整方法是一种高效灵活的专用于设计一维光学超晶格的优化算法,与其他优化算法相比,自调整方法能在更短的时间内搜索出更理想的优化结果。

The majior contributions are summarized as follows:1. Enhanced the concept of min-max transfer capacity, which is the conservative transfer ability against the optimistic transfer ability that ATC evaluates.2. Constructed a TRM model of bi-level optimization based on leader-follower decision-making model, and an analytic method of computing TRM is proposed. A bi-section search algorithm simplifies and speeds up the calculation.3. Proposed the min-max transfer capability model considering steady voltage stability. The BiGA algorithm used in this model is shown to be robust.

本文针对这些问题,补充、提出了一些方法和见解,具体研究成果如下:1、针对ATC评估的是&乐观&情况下电网输电能力,提出了&保守&情况下的电网输电能力-至少传输容量的概念。2、提出基于主从决策的TRM双层优化模型,给出了TRM计算的解析方法,两次一维搜索的算法减小了TRM求解的难度,提高了计算速度。3、提出考虑静态电压稳定约束的至少传输容量评估模型,针对模型特点提出的BiGA算法具有较强的鲁棒性。

Some details in numerical experiment are also presented, such as how to carry out one dimension search, how to set some initial values and how to adjust homotopy parameter.

介绍了在数值试验中一些细节处理,包括如何进行一维搜索,在试验中一些初值的设定,以及同伦参数的调节问题。

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