粒子群算法在农业水文学中的应用进展

The Application of Particle Swarm Optimization in Agricultural Hydrology

优化问题一直是农业水文学研究的重要问题之一,而粒子群算法作为新型智能算法具有很好的寻优能力。介绍了粒子群算法的流程和步骤,以及各种改进后的粒子群算法,分析了粒子群算法在农业水资源优化配置、农田节水灌溉措施、农作物种植优化等农业水文学几个方面的应用现状。结果表明,粒子群算法在农业水文学中的应用范围有限;现有应用研究重视经济效益最大化,忽视社会生态效益;研究呈现碎片化的现象,未形成完整的学科理论体系;改进后的粒子群算法具有更好的寻优能力。指出粒子群算法与其他优化算法和技术结合将会为该算法在农业水文学中的发展开辟新的方向和道路,为农业水文学中科学问题的解决得出更好的优化结果。

The optimization problem has always been one of the important problems in agricultural hydrology research,and particle swarm optimization(PSO)as a new intelligent algorithm has a good optimization ability.This paper introduced the process and steps of particle swarm optimization(PSO),as well as various improved PSO,analyzed the application status of PSO in agricultural hydrology such as optimal allocation of agricultural water resources,water saving irrigation measures for farmland and optimization of crop planting.The results showed that the application of particle swarm optimization in agricultural hydrology was limited.The existing applied research focused on the maximization of economic benefits and ignored the social ecological benefits.The research was fragmented and did not form a complete discipline theory system.The improved particle swarm optimization algorithm had better searching ability.The paper pointed out that the combination of particle swarm optimization(PSO)with other optimization algorithms and techniques will open up a new direction and path for the development of this algorithm in agricultural hydrology and obtain better optimization results for solving scientific problems in agricultural hydrology.