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C++ conversion to python

阳春漆

粒子群算法，也称粒子群优化算法（Particle Swarm Optimization），缩写为 PSO， 是近年来发展起来的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种，和模拟退火算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。粒子群算法是一种并行算法。(Particle swarm optimization (PSO), also called particle swarm optimization (Particle Swarm Optimization), is abbreviated as PSO, which is a new evolutionary algorithm (Evolutionary Algorithm EA) developed in recent years. PSO algorithm is a kind of evolutionary algorithm. It is similar to simulated annealing algorithm. It also starts from the random solution and finds the optimal solution by iteration. It also evaluates the quality of the solution through fitness, but it is simpler than the genetic algorithm rule. It does not have the crossover (Crossover) and the Mutation operation of genetic algorithm. Search for global optimum. This algorithm has attracted the attention of the academic community for its advantages of easy realization, high accuracy and fast convergence, and has shown its superiority in solving practical problems. Particle swarm optimization (PSO) is a parallel algorithm.)

问道清理背包辅助源码 1.6版本清包辅助源码(wendao1.6 empty the trash)

粒子群优化(Particle Swarm Optimization - PSO) 算法是一种新兴的有潜力的进化算法( Evolutionary Algorithm - EA) .PSO 算法,和遗传算法相似,它也是从随机解出发,通过迭代寻找最优解,它也是通过适应度来评价解的品质. 但是它比遗传算法规则更为简单,它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作. 它通过追随当前搜索到的最优值来寻找全局最优。-pso

闽江学院课件第七章，需要的人请下载吧。如果有需要可以联系本人(Chapter VII of Minjiang University courseware)

创建一个数组对其中数据进行操作,包括输出，顺序查找，二分查找，冒泡排序，插入排序。-Create an array of which the data operations, including output, sequential search, binary search, bubble sort, insertion sort.

视频采集,一些源码,供大家参考一下.供大家参考一下-Video Capture, some source code for the U.S. reference. For the U.S. refer to

2019年中鸣超级轨迹赛马达控制例子程序(Example program of motor control for Zhongming Super Track Race in 2019)

高维降低维，最大程度的保存距离之间的差异(High dimension reduces dimension, the maximum degree of preservation distance difference)