用实数编码遗传算法计算最优运输时间

Nimet IŞIK
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引用次数: 0

摘要

电子能量分析仪被设计用来分析特定能量的带电粒子束。该设计基于不同能量的电子在不同时间到达探测器的原理。因为在这些分析仪中,具有不同能量的电子遵循不同的轨道。在碰撞实验中,确定分析器中带电粒子的运动轨迹和传递时间是非常重要的。本文采用实数编码遗传算法,给出了带电粒子迁移时间的最优解。在本研究中,采用试错法获得了遗传算法的超参数和类型。研究结果表明,遗传算法在广泛的数据集上给出了高精度的时间分辨率值。结果表明,遗传算法是解决搜索和优化问题的一种有效方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Calculation of Optimum Transit Times with Real-Coded Genetic Algorithm
Electron energy analysers have been designed to analyse charged-particle beams at specific energies. The design is based on the principle that electrons with different energies arrive at the detector at different times. Since electrons with different energies follow different orbits within these analysers. In collision experiments, it is very important to determine the trajectories and transit times of the charged particles in the analyser. In this study, optimum solutions for transit times of charged particles were provided using a real-coded genetic algorithm. Hyper parameters and types of genetic algorithm were obtained using trial and error methods, in this study. The results of this study indicate that genetic algorithm gives time resolution values in a wide data set with high accuracy. The results show that genetic algorithms (GA) are a fascinating approach for solving search and optimization problems.
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