论文标题
高斯突变在进化遗传算法中的自适应应用
Applications of Gaussian Mutation for Self Adaptation in Evolutionary Genetic Algorithms
论文作者
论文摘要
近年来，由于需要更强大的计算方法，优化问题变得越来越普遍。随着技术的最新出现，例如人工智能，需要新的元硫疗法来增强古典算法的能力。最近，研究人员一直在关注查尔斯·达尔文（Charles Darwin）的自然选择理论和进化论，以此作为使用机器学习来增强当前方法的一种手段。 1960年，第一种遗传算法是由约翰·H·霍兰德（John H. Holland）和他的学生开发的。我们探讨了遗传算法在开发能够使用高斯突变发展的系统中的数学直觉，以及它在解决优化问题方面的影响。
In recent years, optimization problems have become increasingly more prevalent due to the need for more powerful computational methods. With the more recent advent of technology such as artificial intelligence, new metaheuristics are needed that enhance the capabilities of classical algorithms. More recently, researchers have been looking at Charles Darwin's theory of natural selection and evolution as a means of enhancing current approaches using machine learning. In 1960, the first genetic algorithm was developed by John H. Holland and his student. We explore the mathematical intuition of the genetic algorithm in developing systems capable of evolving using Gaussian mutation, as well as its implications in solving optimization problems.
