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normal algorithm相关的网络例句

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The basic theory of the algorithm for test pattern generation using satisfiability is explored, including represent method of SAT-ATPG, search algorithm and analyses of achievement techniques. We describe how to represent circuits and fault detection problem as Conjunctive Normal Form . We improve an effient search algorithm suited to ATPG based on basic satisfiability algorithm.

本文研究了组合逻辑电路测试向量自动生成的可满足性方法,主要进行了可满足性的测试生成原理、实现算法、性能提高和测试向量的最大压缩等方面的研究,改进了一种有效的测试生成搜索算法SAT-ATPG,提出了隐含多路敏化的故障效应单路定向传播方法SOPCA、控制输入跟踪算法CIT和测试衍生算法TD,取得了较显著的效果。

Two normal forms, best-simple normal form and literal normal form, are presented at first in order to eliminate the complexity of formulas decision. Based on the two normal forms, a deduction proof of decidability theorem in L and a decision algorithm P based on deduction for proportional formulas are given and a decision machine found on P, DMBD, is also designed.

首先提出了消解复杂性的两种范式:最简范式和文字范式,在此基础上给出了L的可判性定理的演绎证明及命题公式的演绎判定算法P,并基于ML语言设计了基于P的演绎判定机DMBD。

However, this model is nonlinearity and has mixed discrete variables, and can't be solved by normal algorithm.

但该模型具有非线性、混合离散变量等特点,用常规的优化算法不能求出其最优解。

Lyapunov Equation based algorithm for calculating state feedback gain is a comparatively normal algorithm used in pole assignment.

基于李亚普诺夫方程的状态反馈增益算法是极点配置算法中比较常见的一种。

There are two procedures including solving nonlinear equations and orbit prediction. The difficulty of the problem in this paper rests with interlace and interference of the two nonlinear procedures, which lead dispersion with the normal algorithm.

其难点在于求解非线性方程组和轨道递推两个非线性过程交织在一起,互相干扰,双重的非线性对微小的误差产生的强烈的放大作用,导致使用通常的算法根本无法得到收敛的解。

In this implementation, the evolutionary algorithm is hybridized with the simulated annealing algorithm and the hill climbing heuristic. The main aspects are as follows. The Metropolis criterion of the simulated annealing algorithm is introduced to select the offspring in order to make the algorithm more effective to escape the local optimum. In terms of the hill climbing heuristic, the local normal perturbing mutation operator based probability selecting is developed to enhance the local searching of the algorithm.

其主要工作是将进化算法与模拟退火算法及爬山方法相组合,引入模拟退火算法中Metropolis接受准则选择子代,提高算法跳出局部最优解的能力:借鉴爬山方法思想,构造了基于概率选择的局部正态摄动变异算子,以强化进化算法局部细搜索能力;同时进化算法以多种群方式实现,在降低计算时间的同时提高算法收敛到全局最优解的概率。

On this basis, according to historical data, apply ANN and differential simulation method to get the quantitatively correlative relations between each production and its own influence factors, and introduce the new methods of prediction for dynamic indexes with gas-field development (The combinatorial prediction method based on fuzzy comprehensive evaluation, the method of ANN to select optimally combinatorial prediction models and the ANN prediction method based on genetic algorithm).(2) Base on mathematical programming, combine with quantitative economics and techno-economics, introduce economical indexes to establish production"s distribution optimal model, production"s constitution optimal model and measured production"s constitution optimal model, including multi-objective models and five-years models. Upon this, the optimal project for all gas field and each gas-collected factory can be got. Also, introduce the time value of capitals to improve on these models.(3) Base on the optimal solution theory and algorithm theory for the nonlinear programming problem, introduce the SUMT algorithm and genetic algorithm to study how to solve the models, and on the basis of normal genetic algorithm, make use of auto-adaptively modulating method to improve on normal genetic algorithm; Base on algorithm"s convergence theory and calculation"s complexity theory to analyze seriatim SUMT algorithm"s convergence and genetic algorithms convergence, and compare performance with each other.

在此基础上,利用神经网络方法和微分模拟方法根据历史数据得到各分项产量与其影响因素之间的定量关联关系,并引入气田开发动态指标新的预测方法(基于模糊综合评判的组合预测方法、神经网络优选组合预测模型预测方法以及基于遗传优化的神经网络预测方法);(2)以数学规划为基础,结合数量经济学和技术经济学,引入经济指标建立产量分配优化模型、产量构成优化模型、措施产量构成优化模型、气田开发多目标规划模型以及五年规划模型,进而获得全气田及各采气厂的最优方案,并引入资金时间价值对五年规划模型进行改进;(3)以非线性规划问题的最优解及算法理论为基础,引入SUMT算法以及遗传算法对模型的求解进行研究,并在原有的遗传算法基础上,引入自适应调整方法对遗传算法进行改进;以算法的收敛性理论和计算复杂性理论为基础,逐一分析SUMT算法以及遗传算法的收敛性,并比较三种算法的优劣性。

3D-CTM (Coupled Thermo-Mechanical Forming Simulation) software for precision forging process of aero-engine blade was developed. The key technologies of 3D coupled rigid-viscoplastic thermo-mechanical FEM simulation of blade forging process were studied systematically. By using the remeshing method of contracting from the boundary to the inner, new mesh system from old distorted mesh system can be obtained. A method of modifying the position of nodes touching on the die according to its original normal was proposed to avoid "dead lock" problem due to uncontinuity of normal of scatted die meshes. The pseudo-static iterative algorithm was used to simplify the coupled thermo-mechanical computation. In particular, formulations to determine relaxation factor β was established for rigid viscoplastic FEM adopting penalty function method, and an improved cubic factor rapid algorithm derived from these formulations was proposed by combining with the advantage of advance and retreat search method.

采用基于边界构形的内缩法,实现了三维畸变网格的重新划分;提出了初矢修正法对触模节点的位置进行修正,解决了由于离散的模具网格的法矢不连续造成的&死锁&问题;采用准静态迭代法简化了速度场和温度场耦合计算过程;特别是针对减速因子β的选取,建立了适用于三维复杂成形过程刚粘塑性罚函数法有限元三次因子法的计算公式,并结合进退搜索法提出了改进的三次因子快速算法,提高了模拟计算效率和稳定性,在此基础之上,开发了面向叶片精锻过程的三维刚粘塑性热力耦合有限元模拟分析系统(3D-CTM),系统的可靠性得到了圆柱体镦粗的验证。

Based on the discussion about fitting normal error's definition, constitution and properties, it was suggested that fitting normal error represented the error of fitting plane linear in old highway. The accuracy index of fitting plane linear in old highway based on fitting normal error was set up. The algorithm of swinging approach on compressible size step that could be used to calculate the fitting normal error was put forward. The method and basic norm of decision about fitting normal error's symbolic were discussed.

在论述拟合法线偏差定义、构成及性质的基础上,提出以拟合法线偏差表征旧路平面线形拟合偏差;建立了基于法线偏差的旧路平面线形拟合精度指标;提出了采用步长压缩摆动趋近法计算拟合法线偏差的算法,并就拟合法线偏差的符号判定准则及方法进行了讨论。

After analyzing the shortages of the existing algorithms for frequent pattern clustering,proposes an algorithm for creating compressed partial order based on pattern clustering function.Experiment result shows the compression arithmetic has higher proficiency and qualify,also can obtain much less number and much more information pattern.Thereby can find out more interesting of visited frequent sequential than the normal algorithm.

分析了现有频繁模式聚类算法的不足,提出了在模式聚类函数的基础上生成一个压缩的偏序的算法,实验结果显示该算法可以对频繁序列模式进行高效、高质量的压缩,可以得到数量更少、信息量更大的模式,从而提高发现的频繁访问序列的兴趣性。

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