基于自适应并行遗传算法的泊松曲线沉降预测模型  

Poisson Curve Settlement Forecasting Model Based on Adaptive Parallel Genetic Algorithm

作　　者：谢盛嘉[1] 

机构地区：[1]广东女子职业技术学院,广东广州511450

出　　处：《计算机与现代化》2011年第8期20-22,共3页Computer and Modernization

摘　　要：针对简单遗传算法采用固定的交叉概率和变异概率不能总是满足当前种群的需要,影响算法的性能及效率,采用自适应的交叉概率和变异概率,且将并行技术与遗传算法相结合,提出自适应并行遗传算法,用于泊松曲线沉降预测模型的优化。实验结果表明,该算法为泊松曲线沉降预测模型的参数估计提供了一种有效的方法。The simple genetic algorithm which uses a fixed crossover probability and mutation probability can not always meet the current needs of population,which affects the algorithm performance and efficiency.This paper uses the adaptive crossover probability and mutation probability,unifies the parallel technology and the genetic algorithm,and proposes the adaptive parallel genetic algorithm for Poisson curve settlement forecasting model optimization.The experimental results indicate that,this algorithm provides an effective method for the parameter estimation of Poisson curve settlement forecasting model.

关 键 词：自适应 并行遗传算法 泊松曲线 参数估计 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]