基于混沌变量，提出一种变尺度混沌优化方法。
A mutative scale chaos optimization method is proposed based on the chaos variables.
算例结果表明，混沌优化方法比常规的数值算法和遗传算法更为优越。
Calculation results showed that chaotic optimization method was superior to conventional methods and genetic arithmetics.
鉴于拟变分不等式求解比较困难，设计了基于混沌优化方法的启发式求解算法。
Since it is difficult to solve quasi-variation inequality, the paper designs a heuristic solution algorithm based on chaos met...
鉴于拟变分不等式求解比较困难，设计了基于混沌优化方法的启发式求解算法。
Since it is difficult to solve quasi-variation inequality, the paper designs a heuristic solution algorithm based on cha…
利用优化问题的非线性共轭梯度法与混沌优化方法相结合，提出了一种新的混合优化算法。
A new hybrid algorithm which combines the chaos optimization method and the nonlinear conjugate gradient method approach having an effective convergence property is proposed.
研究了混沌优化方法中混沌变量的初值设定和载波过程中放大倍数等参数调整的实用方法。
How to initialize chaotic variables and determine parameters such as enlanger multiple of carrier_wave in the chaotic optimization method.
基于混沌运动的初值敏感性和对混沌优化搜索过程的分析，提出了并行自适应混沌优化方法。
Based on the initial value sensitivity of chaotic motion and the analysis of optimal searching process, a parallel adaptive chaotic optimization (PACO) method is proposed.
该方法具有逐次优化算法的隐性并行性和收敛性，禁忌搜索的智能性和变尺度混沌优化方法的快速性。
The algorithm has not only the implicit parallelism, global convergence of POA and the intelligence of tabu search, but also the fast convergence of MSCOA.
分析了BP神经网络和混沌优化的特点，并将混沌优化方法和梯度下降法结合起来构成一种新的组合搜索优化方法。
The characteristics of BP neural network and chaos optimal method are analyzed. By integrating chaos optimal method with gradient-decline method, an optimal method of combination search is created.
把BFGS方法与混沌优化方法相结合，基于混沌变量提出一种求解具有变量边界约束非线性最优化问题的混合优化方法。
Combining the BFGS method with the chaos optimization method, a hybrid approach is proposed to solve nonlinear optimization problems with boundary restraints of variables.
变尺度混沌优化（MSCOA）是一种改进的混沌优化方法（COA），利用混沌运动的内在随机性、遍历性和规律性进行全局寻优；
Mutative scale chaos optimization algorithm (MSCOA) is a modified chaos optimization algorithm (COA), which possesses the properties of randomness, ergodicity and regularity of chaos movement.
算例表明，当混沌搜索的次数达到一定数量时，混合优化方法可以保证算法收敛到全局最优解，且计算效率比混沌优化方法有很大提高。
Numerical examples illustrate that the present method possesses both good capability to search global optima and far higher convergence speed than that of chaos optimization method.
为了避免模糊控制器设计过程中参数的大量调试工作，并使其具有最佳的控制性能，本文首次将混沌优化方法应用于模糊控制器参数设计。
In order to improve the control performance and avoid a great deal of adjusting work of the parameters, we applied chaos optimization method in design of fuzzy controller firstly.
考虑神经网络在训练大规模样品时易陷入局部极小，用梯度下降法与混沌优化方法相结合，使神经网络实现快速训练的同时，避免陷入局部极小。
Combining grading method with chaotic optimization, the neural network model achieves rapid training and avoids local minimum when there are a lot of samples to be trained.
对于模型的求解方法，构造了一种自适应的混沌遗传算法，采用自然数编码方式，动态的在线调整算法的交叉和变异概率，并采用混沌优化方法作为变异算子。
The algorithm used natural number coding method with dynamically adjustment for the probability coefficients of crossover and mutation, and used chaos optimization method as the mut.
提出一种关于多层前向神经网络结构的混沌优化设计方法。
The optimization design method is proposed for feed-forward neural network structure by means of chaos ergodicity and randomicity.
最后采用混沌优化法来获得多阈值模糊互信息分割方法的最佳阈值。
Finally, the optimal thresholds of image segmentation based on fuzzy mutual information is obtained by means of chaos optimization method.
针对混沌时间序列的最近邻域预测法，提出了改进的最近邻域点优化选择方法和加权一阶局域线性预测法。
Optimal choice method of the nearest neighboring points and adding weight one-rank local region method is introduced on the nearest neighboring forecasting method of chaotic time series.
基于混沌优化算法给出了求解最优超订水平的方法。
The solving method for the optimal solution of the overbooking model is given based on chaos optimization algorithm.
提出了一种基于混沌相空间重构理论的优化近邻点局部线性化跳频预测方法。
Based on the theory of chaos phase space reconstruction, a local linear forecasting approach on selecting the optimal neighbor points is presented in this paper.
提出了一种基于混沌优化的PID控制器参数整定方法。
A method is proposed for parameters tuning of normalized PID controller with chaos variables.
本文给出了一种新的全局优化问题的计算方法—混沌退火算法，并将其应用于非线性速度反演计算。
A new successive overall optimization calculation method-chaotic annealing will be used in the solution and non-linear velocity inversion calculation.
基于混沌变量，提出一种混沌模拟退火优化方法，给出了初始温度的确定方法。
Based on chaotic variable, a chaos simulated annealing algorithm is proposed and the method of defining the initial temperature is given.
本文分析了该类VRP问题的数学模型，提出了一种针对该问题的混沌优化算法，介绍了具体的编码方法和实现算子。
The mathematic model of this VRP is analyzed, and a chaos optimization algorithm is proposed, then the coding method and compute operators are introduced in this paper.
本文分析了该类VRP问题的数学模型，提出了一种针对该问题的混沌优化算法，介绍了具体的编码方法和实现算子。
The mathematic model of this VRP is analyzed, and a chaos optimization algorithm is proposed, then the coding method and compute operators are introduced in this paper.
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