基于H-PSO算法的电水转换参数优化研究

Research on optimization of electric-water conversion parameters based on H-PSO algorithm

通过构建合适的电水转换模型,可以有效地解决农业灌溉用水智能化计量的问题。文中通过研究电水转换模型,进一步提高搜索能力,克服粒子群算法易陷入局部最优的缺陷,提出了一种基于杂交策略的改进粒子群算法。该算法对整个解空间实行全局搜索,避免粒子陷入"早熟",并在迭代过程中让部分粒子杂交,提高搜索精度。仿真结果表明:与标准的粒子群算法相比,文中提出的改进粒子群算法收敛速度加快50%,误差率降低了3%~4%。

By constructing a suitable electric-water conversion model,the problem of smart measurement of agricultural irrigation water can be effectively solved.This paper raises an improved particle swarm optimization algorithm based on hybrid strategy by researching on electric-water model,which further improve the searching capability to overcome the imperfection of the particle swarm algorithm that is easy to fall into the local optimum.The algorithm performs a global search on the entire solution space to avoid particles falling into“premature”,and allows some particles to hybridize in the iterative process to improve search accuracy.The simulation result shows that compared with the standard particle swarm algorithm,the hybrid strategy-based particle swarm algorithm converges 50%faster,and reduces the error rate by 3%to 4%.