...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Natural Computing >A Swarm Intelligence Based (SIB) method for optimization in designs of experiments
【24h】

A Swarm Intelligence Based (SIB) method for optimization in designs of experiments

机译：一种基于群体智能（SIB）的实验设计优化方法

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Natural heuristic methods, like the particle swarm optimization and many others, enjoy fast convergence towards optimal solution via inter-particle communications. Many applications of such methods are applied to the optimization in engineering, but only a few to the optimization in statistics. It is especially difficult to implement in the optimization problems of experimental designs as the search space is mostly discrete, while most natural heuristic methods are limited to searching continuous domains. This paper introduces a new natural heuristic method called Swarm Intelligence Based method for optimizing problem with a discrete domain. It includes two new operations, MIX and MOVE, for combining two particles and selecting the best particle respectively. This method is ready for the search of both continuous and discrete domains, and its global best particle is guaranteed to monotonically move towards the optimum. Several demonstrations on the optimization of experimental designs are given at the end of this paper.
机译：自然启发式方法，例如粒子群优化和许多其他方法，通过粒子间通信迅速朝着最优解收敛。这种方法的许多应用都被应用于工程学的优化中，但是只有少数几个应用于统计数据的优化中。由于搜索空间大部分是离散的，而大多数自然启发式方法仅限于搜索连续域，因此在实验设计的优化问题中尤其难以实现。本文介绍了一种新的自然启发式方法，称为基于群体智能的方法，用于优化离散域的问题。它包括两个新操作，MIX和MOVE，用于合并两个粒子并分别选择最佳粒子。该方法已准备好搜索连续域和离散域，并且保证了其全局最佳粒子单调地朝最优方向移动。最后，对实验设计的优化进行了一些演示。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号