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基于混合加速粒子群算法的捕食者-食饵模型参数估计
  • ISSN号：1001-9626
  • 期刊名称：《生物数学学报》
  • 时间：0
  • 分类：O212.1[理学—概率论与数理统计;理学—数学]
  • 作者机构：[1]池州学院数学与计算机科学系,安徽池州247100, [2]西北师范大学数学与统计学院,甘肃兰州730070
  • 相关基金：国家自然科学基金（11061031,10871160）; 池州学院自然科学研究重点项目（2012ZRZ010）
作者： 曹怀火[1], 李海燕[1], 伏升茂[2]
关键词： 捕食者-食饵模型, 参数估计, 混合加速粒子群算法, Predator-prey model, Parameter estimation, Hybrid acceleration particle swarm optimization
中文摘要：

首先应用四阶紧致差分格式,对捕食者-食饵模型的参数估计转化为相应的优化问题,然后将加速粒子群算法与Nelder-Mead算法相结合,提出混合加速粒子群算法,用来优化模型参数.数值实验中,借助四阶龙格-库塔算法对模型进行仿真计算,与观测值比较表明该算法是可行的.

英文摘要：

The parameter estimation problem of prey-predator model was transformed into the corresponding optimization problem by the use of fourth-order compact difference scheme in the paper.The hybrid algorithm of acceleration particle swarm optimization and Nelder-Mead algorithm was proposed to optimize the parameters of model.In the numerical experiments,Fourth-order Runge-Kutta algorithm was used to compute the model,and comparing the simulation results with observed values.The results of comparing show that the algorithm is feasible.

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期刊信息
  • 《生物数学学报》
  • 北大核心期刊（2008版）
  • 主管单位:中国数学会
  • 主办单位:中国数学会生物数学学会
  • 主编：陈兰荪
  • 地址：辽宁省鞍山师范学院158号
  • 邮编：114007
  • 邮箱：smbjbm@tom.com
  • 电话：0412-2960893
  • 国际标准刊号：ISSN：1001-9626
  • 国内统一刊号：ISSN：34-1071/O1
  • 邮发代号:
  • 获奖情况:
  • 国内外数据库收录:
  • 美国数学评论（网络版）,德国数学文摘,日本日本科学技术振兴机构数据库,中国北大核心期刊（2004版）,中国北大核心期刊（2008版）
  • 被引量:5686