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。
This paper presents an optimization algorithm based on chaotic simulated annealing algorithm, which is used to estimate the parameter of Nonlinear Muskingum model.
本文主要研究混沌模拟退火神经网络(CSAN)在求解tsp中的应用。
In this paper, We mainly do researches on using chaotic neural network based on simulated annealing (CSAN) to solve TSP.
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.
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