Research on Optimal Scheduling of Water Supply System Based on Particle Swarm Algorithm
Research has been conducted on the improvement of particle swarm optimization algorithm,and the idea of penalty function method has been combined to improve the adaptive inertia particle swarm algorithm.The maximum inertia coefficient ω val-ue is given within the feasible range,and when the particles reach the peak valley,the ω value is dynamically adaptively lowered.Based on this characteristic,the particle swarm iteration formula has been updated.The focus is on analyzing and comparing the maximum and average data of three particle swarm optimization algorithms before and after improvement under four test functions.The particle swarm optimization algorithm that is more suitable for this model is compared,and the improved adaptive inertial parti-cle swarm optimization algorithm achieves certain improvements in convergence accuracy and speed.And the standard test function is used to analyze and compare the particle swarm optimization algorithm before and after improvement.The results show that the convergence speed and accuracy of the improved particle swarm optimization algorithm are improved,and it can effectively balance the ability of global search and local search.Based on the optimization scheduling model established in the previous stage,the actu-al data of the water plant is predicted,and the optimization scheduling plan is determined.
万方数据
维普
