城市轨道车辆阻力公式经验参数文化基因优化算法的研究

发布时间：2018-04-05 22:31

  本文选题：文化基因算法　切入点：遗传算法　出处：《计算机应用研究》2017年12期

【摘要】：为了解决城市轨道车辆阻力公式经验参数不易精确求解的问题,提出了一种改进的文化基因优化算法。首先,基于城市轨道车辆运行阻力经验公式和实际的运行数据,建立了城市轨道车辆运行阻力经验参数最优化问题的数学模型。为提升算法性能以提高求解精度,结合了遗传算法全局搜索能力强与粒子群算法收敛速度快的特点,进行优势互补,构造了一种混合算法以便于全局搜索。其次,结合方程组求解法求解速度快和爬山法局部搜索能力强的特点,构造了一种混合算法以便于局部搜索。最后,在MATLAB 2010a GUI平台下采用几种不同的经验参数辨识算法和优化算法进行仿真实验。仿真结果表明,在相同条件下改进的文化基因优化算法能够寻到更精确的阻力公式经验参数。
[Abstract]:In order to solve the problem that the empirical parameters of the resistance formula of urban rail vehicles are not easy to be solved accurately, an improved cultural gene optimization algorithm is proposed.Firstly, based on the empirical formula of the running resistance of urban rail vehicle and the actual operation data, the mathematical model of the optimization problem of the empirical parameters of the operation resistance of the urban rail vehicle is established.In order to improve the performance of the algorithm and improve the accuracy of the algorithm, a hybrid algorithm is constructed to facilitate the global search by combining the advantages of the genetic algorithm and the fast convergence speed of the particle swarm optimization algorithm.Secondly, a hybrid algorithm is constructed to facilitate local search by combining the fast speed of solving equations and the strong local search ability of mountain climbing method.Finally, several kinds of empirical parameter identification algorithms and optimization algorithms are used to simulate on MATLAB 2010a GUI platform.The simulation results show that the improved cultural gene optimization algorithm under the same conditions can find more accurate empirical parameters of the resistance formula.
【作者单位】： 大连海事大学信息技术学院;内蒙古民族大学机械工程学院;
【基金】：国家自然科学基金资助项目(60574018)
【分类号】：TP18
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本文编号：1716784