Rough set-based method of combinatory logic optimization was presented by using knowledge expression of logic function with rough set theory, and its corresponding algorithm was given, also.
运用粗集理论对逻辑函数进行知识表达的方法，提出了基于粗糙集的组合逻辑优化方法，并给出了相应的算法。
The objective function for evaluating the data link system is proposed, and then the system optimization algorithm and optimal results are presented.
提出一种评价数据链路系统性能的目标函数，设计了数据链路系统的优化设计算法，并给出其优化结果。
The simulation of some test function optimization using BCC algorithm shows BCC algorithm a kind of potentially powerful optimization method worth of much more research.
对不同函数优化试例的仿真表明细菌群体趋药性算法性能良好，是一种具有进一步研究价值的集群函数优化方法。
Function optimization experiments show that which operator works better in an algorithm depends on both the combination capability of the operator and the problem to be optimized.
函数优化实验研究表明，在算法中采用何种离散重组算子较为合适与算子的组合能力有关，也与优化问题有关。
The optimization result of multi-peak value function shows that the algorithm presented can solve premature convergence problem effectively and converge to the globally optimal solution.
多峰值函数优化结果表明，该算法可以有效地解决早熟收敛问题，更易达到全局最优解。
The classical Particle swarm optimization (PSO) algorithm is a powerful method to find the minimum of a numerical function, on a continuous definition domain.
经典的粒子群优化算法是一个在连续的定义域内搜索数值函数极值的很有效的方法。
Aimed at particle swarm optimization (PSO) algorithm being easily trapped into local minima value in multimodal function, a rotating surface transformation (RST) method was proposed.
针对粒子群优化算法(PSO)应用于多极值点函数易陷入局部极小值，提出旋转曲面变换(RST)方法。
This paper proposes a new global optimization technique in which combines the filled function method and BP algorithm for Training feedforward neural networks.
把填充函数法与BP算法相结合，提出一种训练前向神经网络的混合型全局优化新算法。
Particle Swarm Optimization (PSO) algorithm is a powerful method to find the extremum of a continuous numerical function.
微粒群优化算法是求解连续函数极值的一个有效方法。
It gives an interval enclosure for filled function and presents an interval filled function algorithm to solve this nonsmooth optimization.
给出了填充函数的区间扩张，并提出了求解该非光滑优化问题的区间填充函数算法。
Because of its function to automatically delete redundant nodes, the optimization ability of this algorithm is prominent.
由于算法自动删除冗余节点的功能，突出了优化能力。
An improved particle swarm optimization (PSO) algorithm was designed. And a weighted ITAE index of turbine speed error was taken as the fitness function of the improved PSO algorithm.
提出了一种新的改进的粒子群优化算法，并以水轮机转速偏差的加权ITAE指标作为改进粒子群优化算法的适应度函数。
The optimization result of multi-peak value function shows that the algorithm introduced can converge to the globally optimal solution effectively.
多峰值函数优化结果表明，该算法能更有效地达到全局最优解。
It makes a searching for all local optimization of the multimodal function that a PSO algorithm based on chaos sequence for multi-modal function optimization.
基于混沌序列的多峰函数微粒群寻优算法的目标就是找到多峰函数的所有局部优化峰值。
The performance of DE algorithm is superior to other algorithm in numerical function optimization.
其中，差分演化算法在数值函数优化方面的性能要优于其它的优化算法。
This paper based on ambiguity function theory analyzes the cause of cross-components and gives the optimization algorithm of adaptive TFD with radially-gaussian kernel.
文中以模糊函数理论为基础，分析了时频分析产生交叉项的原因，给出了以径向高斯函数为核函数的自适应时频分析优化算法。
The mutation strategy was improved so that the optimized DE algorithm performance was further improved on function optimization.
通过对差分演化算法的变异策略改进，使优化后的差分演化算法在函数优化方面性能得到进一步提高。
The efficiency of the proposed algorithm was analyzed. The simulation of function optimization and fashion design indicates the mutation strategy and the algorithm is effective.
给出了算法设计实施中关键问题的处理，分析了算法的效率，并通过函数优化和服装设计问题的仿真实验验证变异策略和算法的有效性。
The efficiency of the proposed algorithm was analyzed. The simulation of function optimization and fashion design indicates the mutation strategy and the algorithm is effective.
给出了算法设计实施中关键问题的处理，分析了算法的效率，并通过函数优化和服装设计问题的仿真实验验证变异策略和算法的有效性。
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