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基于混沌粒子群优化算法的灰色GM(1,1)模型在地下水埋深预测中的应用
引用本文:盖兆梅,付强,刘仁涛.基于混沌粒子群优化算法的灰色GM(1,1)模型在地下水埋深预测中的应用[J].数学的实践与认识,2008,38(11):67-72.
作者姓名:盖兆梅  付强  刘仁涛
作者单位:1. 东北农业大学,水利与建筑学院,哈尔滨,150030
2. 黑龙江建筑职业技术学院,哈尔滨,150025
摘    要:将混沌优化算法与粒子群优化算法相结合,形成新的混沌粒子群优化算法.利用混沌运动的遍历性,避免陷入局部最优.同时,粒子群算法能加快混沌优化算法的收敛速度,使搜索效率得到提高.用混沌粒子群优化算法优化灰色GM(1,1)模型中的参数,通过横向和纵向比较,优化效果良好,模型预测精度得到了提高.运用该模型对三江平原地下水埋深进行动态预测,预测结果可为有关决策部门提供参考.

关 键 词:三江平原  混沌  粒子群  优化  预测
修稿时间:2007年12月14

Grey GM(1,1) Model Based on Chaotic Particle Swarm Optimization Algorithm and Its Application in Groundwater Dynamic Prediction
GAI Zhao-mei,FU Qiang,LIU Ren-tao.Grey GM(1,1) Model Based on Chaotic Particle Swarm Optimization Algorithm and Its Application in Groundwater Dynamic Prediction[J].Mathematics in Practice and Theory,2008,38(11):67-72.
Authors:GAI Zhao-mei  FU Qiang  LIU Ren-tao
Abstract:Combining chaos optimization algorithm with particle swarm optimization algorithm,the new algorithm that chaotic particle swarm optimization algorithm is established.Taking advantage of chaotic ergodicity,it can avoid trapping into the local optimum.At the same time,the convergence rate is accelerated by particle swarm optimization algorithm.The parameters of grey GM(1,1) model are optimized by chaotic particle swarm optimization algorithm.Predict precision of the model is examined by two ways,and the result shows that the optimized effect is good and the predict precision of the model is improved.The model predicts the groundwater deep of Sanjiang Plain.The predictive result can provide reference for the relevant decisionmaking department.
Keywords:Sanjiang Plain  chaos  particle swarm  optimization  predict
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