This paper presents an improved fast simulated annealing algorithm based on the analysis on deterministic method and simulated annealing algorithm for solving global optimization problems.
基于对求解全局优化问题的确定性方法和模拟退火算法的分析，文中提出了一种改进的快速模拟退火算法。
Through embedding a gradient descend operator into the generic algorithm, a hybrid algorithm is achieved with fast convergence and great probability for global optimization.
在遗传算法中嵌入一个梯度下降算子，使得混合算法既有较快的收敛性，又能以较大概率得到全局极值。
A fast stochastic global optimization algorithm, particle group optimization algorithm, was used for training the fuzzy neural network.
模糊神经网络的学习算法采用的是快速的粒子群优化算法。
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