A Novel Simultaneous Perturbation Stochastic Approximation Particle Swarm Optimization Algorithm for Agricultural Acreage Evaluation

摘要

In order to solve the shortcomings of traditional Particle Swarm Optimization (PSO) algorithm, this study is to propose a simultaneous perturbation stochastic approximation particle swarm optimization algorithm and its application in agricultural acreage evaluation. In this experiment, regression model is optimized by simultaneous perturbation stochastic approximation particle swarm optimization algorithm and traditional PSO algorithm respectively to show the superiority of simultaneous perturbation stochastic approximation particle swarm optimization algorithm to traditional particle swarm optimization algorithm in agricultural acreage evaluation. The experimental results show that the optimal performance of simultaneous perturbation stochastic approximation particle swarm optimization algorithm is better than that of traditional particle swarm optimization algorithm and application of simultaneous perturbation stochastic approximation particle swarm optimization algorithm in agricultural acreage evaluation is feasible.