设计了模糊随机模拟算法。
Some algorithms about fuzzy random simulations are designed.
模拟退火算法是一种用于解决连续、有序离散和多模态优化问题的随机优化技术。
SA is a stochastic optimization technique that has been used to solve continuous, order discrete and muti-modal optimization problems.
在序列运算理论基础上提出了一种用于多节点系统的随机生产模拟新算法。
Based on the sequence operation theory, a novel algorithm of probabilistic production simulation for a multi-area power system is proposed.
进化算法也称演化算法，是一种模拟自然进化过程的随机优化方法。
Evolutionary algorithm called evolutionary algorithms is a kind of stochastic optimization methods by simulating natural evolutionary process.
并针对电网故障的随机性特点，在面向对象环境中实现了对随机故障的模拟，同时用深度优先算法进行了快速的拓扑跟踪。
To accord with the network malfunction's randomicity, the stochastic malfunction simulation and realizes the topology tracking using the DFS in objected-oriented environment are realized.
引入现代控制科学离散事件动态系统摄动分析思想，提出通信网络随机模拟的快速并行算法。
In this paper, we extend the idea of DEDS (Discrete Event Dynamie System) theory and present a fast parallel algorithm for communication network random simulation.
推广了单噪声驱动系统的二阶随机龙格库塔数值模拟算法，使之适用于关联白噪声和色噪声共同驱动的系统这一更为复杂的情况。
The second order stochastic Runge Kutta algorithm for systems driven by a single additive noise is generalized, which makes it more suitable for complex situation.
针对整数规划全局优化问题所首次提出的模拟植物生长算法，是一种源于大自然的仿生类随机算法。
Plant growth simulation algorithm aiming at the global optimization of integer programming is a kind of bionics random algorithm which occurs in nature.
本文研究能用随机事件图模拟的指挥控制系统信息处理瓶颈的分析算法。
This paper focuses on bottlenecks analysis algorithm of information processing for command and control system via stochastic event graphs.
快速多极算法作为边界元法的求解算法，从而使边界元法能够对含有大量随机分布颗粒的复合材料进行大规模模拟。
Fast multipole method is used as a fast solver for BEM, making BEM applicable for large scale simulation of composites with a large number of randomly distributed particles.
具体表现在：由于模拟进化算法的随机性，不能保证每次计算都能收敛到全局最优解，同时还存在“早熟”现象；
The drawbacks of simulated evolutionary algorithms are that the global optimality can not be always guaranteed because of randomicity and premature con vergence.
基于粒子群算法运用随机模拟和模糊模拟相结合的技术，给出了一种求解该规划模型的混合智能算法。
Desgined a mixed intelligent arithmetic by using the technique of combing the stochastic simulation with fuzzy simulation and particle swarm optimization algorithm to solve this kind of problems.
并用随机数来模拟TSP中每两个城市之间的不同路径，对算法作进一步的讨论。
Further discussions on this algorithm are also carried out by using the random number to simulate the different paths between each two cities in TSP.
通过计算机仿真，验证了该算法对初值的鲁棒性和复原的效果优于基于均匀分布随机扰动量模拟退火盲解卷积算法，提高了收敛到最优解的速度。
Simulation results show that the improved method has better quality, robustness and speed of convergence comparing with simulated annealing algorithm based on uniform distribution random perturbation.
针对模拟退火和遗传算法的参数和操作选取问题，通过将其描述为随机优化问题，提出了基于OCBA的解决方法。
Aimed at the problem of selecting suitable parameters and operators for SA and GA, an OCBA based approach is proposed by formulating the considered problem as a stochastic optimization problem.
搜索技术，诸如遗传算法，模拟退火算法，禁忌搜索和随机移动算法，已经广泛应用于全局优化。
Search techniques such as Genetic Algorithms, Simulated Annealing, Tabu Search and Random Walk Algorithms have been used extensively for global optimization.
人工蚁群算法是一种新型的模拟进化算法，也是一种随机型智能搜索寻优算法。
Artificial ant algorithm is a novel simulated evolutionary algorithm, also a newly stochastic and intellectual searching optimization.
采用遗传算法和蒙特卡洛随机模拟相结合对上述随机优化模型进行求解。
The Genetic Algorithms combined with Monte Carlo Algorithms (MC) is introduced for solving the problems.
通过实验设计，用大量随机数据进行了模拟和统计分析。结果表明，最小偏差算法是一种合理的、实用的、有效的算法。
Numerous simulation experiments and statistical analyses show that he minimum deviation algorithm is a reasonable, effective and applicable algorithm.
通过实验设计，用大量随机数据进行了模拟和统计分析。结果表明，最小偏差算法是一种合理的、实用的、有效的算法。
Numerous simulation experiments and statistical analyses show that he minimum deviation algorithm is a reasonable, effective and applicable algorithm.
应用推荐