中文说明：资源描述 GA_PSO 遗传算法的寻优计算 遗传算法(Genetic Algorithm)是一类借鉴生物界的进化规律(适者生存，优胜劣汰遗传机制)演化而来的随机化搜索方法。它是由美国的J.Holland教授1975年首先提出，其主要特点是直接对结构对象进行操作，不存在求导和函数连续性的限定;具有内在的隐并行性和更好的全局寻优能力;采用概率化的寻优方法，能自动获取和指导优化的搜索空间，自适应地调整搜索方向，不需要确定的规则。遗传算法的这些性质，已被人们广泛地应用于组合优化、机器学习、信号处理、自适应控制和人工生命等领域。它是现代有关智能计算中的关键技术。
English Description：
Application backgroundOptimization calculation of GA_PSO genetic algorithmGenetic algorithm (GA) is a type of reference in the field of biology evolution (survival of the fittest, survival of the fittest genetic mechanism) evolution and random search method. It is by the American professor J. Holland in 1975, was the first to put forward, and its main characteristics is to operate directly on the structure of the object, there is no derivation and limited function continuity; has the inherent implicit parallelism and global searching ability; using a probability optimization method, can automatically access and guidance to optimization of the search space, adaptively adjust the search direction, does not need to determine the rules. The properties of genetic algorithms have been widely used in the fields of combinatorial optimization, machine learning, signal processing, adaptive control and artificial life. It is the key technology of modern intelligent computing.