基于ABC算法的随机数生成误差优化

2021 International Conference of Modern Trends in Information and Communication Technology Industry (MTICTI) Pub Date : 2021-12-04 DOI:10.1109/MTICTI53925.2021.9664773

Ghadir Alselwi, Tugrul Tasci

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引用次数: 0

摘要

优化是在目标函数的设置中找到最佳选项的努力。本研究的目的是利用人工蜂群(Artificial Bee Colony, ABC)算法对多变量函数进行优化，模拟蜜蜂的觅食活动。ABC算法的性能已经在22个基准函数的最小化过程中进行了测量，包括流行的Griewank, Rastrigin, Sphere和Rosenbrock。实验结果表明，ABC算法与实际值较为接近，准确率为98.85。

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Error Optimization in Random Number Generation Using ABC Algorithm

Optimization is an effort to find the best option in the settings of the objective function. The goal of this study is to optimize multivariable functions using Artificial Bee Colony (ABC) which is one of the most current swarm intelligence-based algorithms, simulating the foraging activity of honeybees. The performance of the ABC algorithm has been measured on the minimization process of 22 benchmark functions including the popular Griewank, Rastrigin, Sphere, and Rosenbrock. The experimental results demonstrate that the ABC algorithm has approximated the actual value with an accuracy percentage of 98.85.

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2021 International Conference of Modern Trends in Information and Communication Technology Industry (MTICTI)

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