Calculation results showed that chaotic optimization method was superior to conventional methods and genetic arithmetics.
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。
In the mean time, the convergence of the improved chaotic optimization algorithm and hybrid optimization algorithm are proved.
同时对改进的混沌优化算法和混合优化算法的收敛性进行了证明。
In the third part, the prediction model of fuzzy optimal selection neural network based on chaotic optimization algorithm is studied.
第三部分对基于混沌优化算法的模糊优选神经网络预测模型进行研究。
How to initialize chaotic variables and determine parameters such as enlanger multiple of carrier_wave in the chaotic optimization method.
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。
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.
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。
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.
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。
At the initial stage, chaotic optimization algorithm is used to search a global initial point. Then, a BFS algorithm is adopted to complete the parameters-optimized process.
该算法在起始阶段利用混沌优化算法寻找初始点，随后采用BFS法完成参数寻优过程。
The Chaotic neural network model can be used to solve many multi-dimensioned, discrete, non-convex, nonlinear constrained optimization problems.
基于混沌神经网络模型可以有效地解决高维、离散、非凸的非线性约束优化问题。
The research results show that the chaotic neural networks are more effective than other existing neural networks to solve associative memory and complex optimization problems.
已有的研究结果表明，混沌神经网络在求解复杂优化问题和联想记忆等方面比现有网络有着更好的性能。
An optimization algorithm design based on chaotic variable is proposed for multilayer fuzzy neural network.
提出了一种基于混沌变量的多层模糊神经网络优化算法设计。
The optimization of chaotic synchronization.
混沌同步的优化。
A coupled optimization algorithm combined gradient search with chaotic search is proposed and its (convergence) is discussed.
提出一种混沌梯度组合全局优化算法，并对该算法进行了收敛性分析。
This paper presents an optimization algorithm based on chaotic simulated annealing algorithm, which is used to estimate the parameter of Nonlinear Muskingum model.
提出了用混沌模拟退火法估计非线性马斯京根模型参数的优化算法。
In this paper, the optimization design for self-adaptive control system of feed-forward neural network is proposed based on chaotic variable.
基于混沌变量，提出一种神经网络自适应控制系统的优化设计方案。
Chaotic mechanism is introduced to normal BP algorithm, and the problem of local limit value for network is solved using global moving characteristic of chaotic mechanism is weight optimization.
将混沌机制引入常规BP算法，利用混沌机制固有的全局游动，逃出权值优化过程中存在的局部极小点，解决了网络训练易陷入局部极小点的问题。
The chaotic artificial fish-swarm algorithm is presented combining the artificial fish-swarm algorithm with water resources optimization.
对人工鱼群算法进行了改进，结合灌区优化配水问题，建立了灌区优化配水的混沌人工鱼群算法模型。
This paper studied the chaotic neural network and applied it to a typical combinatorial optimization problem and broadband matching network design.
本文以混沌神经网络为主要研究对象，并应用于典型组合优化问题求解和宽带匹配网络设计之中。
A new successive overall optimization calculation method-chaotic annealing will be used in the solution and non-linear velocity inversion calculation.
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。
The simulation results show that the coupled algorithm is able to make full use of the quickness of gradient search and the ability of global optimization of chaotic search.
仿真结果表明，耦合算法能够充分利用梯度搜索的快速性和混沌搜索全局优化的能力。
The global optimal solution is obtained based on chaotic particle swarm optimization algorithm.
基于混沌粒子群优化算法对优化数学模型进行了求解。
A control method was proposed, which combines the human-imitating control theory and the optimization capability of chaotic neural networks (CNN).
提出一种基于混沌神经网络(CNN)的拟人智能控制方法。
A control method was proposed, which combines the human-imitating control theory and the optimization capability of chaotic neural networks (CNN).
提出一种基于混沌神经网络(CNN)的拟人智能控制方法。
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