遗传算法及其图像识别应用研究：原理、实现及效果分析

摘要：遗传算法是一种模拟自然进化的搜索算法，具有简单易行、鲁棒性强等特点，不需要专门的领域知识，仅用适应度函数作为评价指导搜索过程。在各个领域得到了广泛应用，并取得了许多显著成果，引起学者和工程人员的关注。本文简要介绍了遗传算法的发展历史、研究现状、生物学、数学基础，并详细分析了遗传算法的基本概念、原理、实现技术，包括编码、适应度函数、遗传操作、参数规则等。最后基于遗传算法的程序设计原则，在图像识别中进行了应用并进行了实际效果检验。 关键词：遗传算法，适应度函数，图像识别 Abstract: Genetic algorithm is a searching method simulating natural evolution, which is simple, easy to implement, and robust, it does not require specialized domain knowledge, and only uses fitness function as evaluation to guide the search process. It has been widely applied in various fields, achieving remarkable results and attracting the attention of scholars and engineers. This paper briefly introduces the development history, research status, biological and mathematical basis of genetic algorithm, and analyzes the basic concept, principles, and implementation techniques of genetic algorithm in detail, including encoding, fitness function, genetic operations, parameter rules, etc. Finally, based on the programming principles of genetic algorithm, the application in image recognition is implemented and the actual effect of genetic algorithm is tested. Keywords: Genetic algorithm, fitness function, image recognition