Search - parallel PSO

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[AI-NN-PR] PathPlanningforMobileRobotsBasedontheNeuralNetwork DL : 0: ：针对移动机器人传统路径规划算法效率不高，寻优能力差等问题，提出一种基于神经网络和粒子群优化算法相结合的移动机器人路径规划方法．该方法利用神经网络实现大量的并行和分布计算，发挥PSO简单、容易实现的优点，提高了路径规划的计算效率和可靠性．仿真结果表明，这种新路径规划方法是可行且有效的．-The quality and eficiency of calculation is the two puzzling problems in the tradi— tional algorithm for the robot path planning．In this paper，a new method of obstacle avoidance and path planning based on neural network and particle swarm optimization is proposed．In this method，a neural network is used to realize substantive parallel and distributed compu— ting．And also this exerts the merit of PSO，which improves the computational eficiency and reliability．As it is proved by analysis and test，that a better result is obtained by the pro— posed algorithm．
Date : 2025-12-31 Size : 159kb User : 王风
[AI-NN-PR] MyPsoClerc DL : 0: 本粒子群优化算法（Particle Swarm Optimization）名称：基本粒子群优化算法（PSO）作用：求解优化问题说明：全局性，并行性，高效的群体智能算法 -The particle swarm optimization algorithm (Particle of Swarm Optimization) name: Particle Swarm Optimization algorithm (PSO) Role: solving optimization problems Description: global, parallel, efficient group of intelligent algorithm
Date : 2025-12-31 Size : 4kb User : feilong
[AI-NN-PR] MyPsoGbest DL : 0: 粒子群優化算法（粒子群優化）名稱：粒子群優化算法（PSO）作用：解決優化問題說明：全局，並行，高效的智能算法組-The particle swarm optimization algorithm (Particle of Swarm Optimization) name: Particle Swarm Optimization algorithm (PSO) Role: solving optimization problems Description: global, parallel, efficient group of intelligent algorithm
Date : 2025-12-31 Size : 4kb User : feilong
[AI-NN-PR] PSO-Python DL : 0: 粒子群算法，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。(The particle swarm optimization (PSO) algorithm, which is one of the evolutionary algorithms, is similar to the simulated annealing algorithm. It also starts from the random solution to find the optimal solution by iteration. It also evaluates the quality of the solution by the fitness, but it is more simple than the genetic algorithm rule, and it has no genetic algorithm "Crossover" and "variation". "(Mutation) operation, it seeks the global optimum by following the best value that is currently searched. 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.)
Date : 2025-12-31 Size : 4kb User : 绝情逆空