【摘要】 把土壤水分运移参数的拟合按照模型参数的辨识和优化问题来考虑,将粒子群优化(PSO)算法应用到土壤水分运移参数的辨识和优化中,通过仿真及与其它参数辨识和优化方法的比较表明,PSO算法得出的模型参数优于自适应免疫遗传算法和最小二乘算法,具有简单、精度高、速度快、与初值无关和全局收敛等优点,是一种土壤水分运移参数辨识和优化的新方法。更多还原

【Abstract】 Particle swarm optimization(PSO) originating from artificial life and evolutionary computation is a algorithm.The algorithm completes the optimization through following the personal best solution of each particle and the global best value of the whole swarm.The simulation of parameters estimation of soil water movement model shows that PSO algorithm better identification precision than adaptive immune genetic algorithm(AIGA) and Recursive Least Square(RLS) method.PSO is efficient and effective.The result knows that PSO is a new identification and optimization method in soil water movement parameter.更多还原