• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies >A space transformational invasive weed optimization for solving fixed-point problems
【24h】

A space transformational invasive weed optimization for solving fixed-point problems

机译：用于解决固定点问题的空间变革侵略性杂草优化

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Real life problems are used as benchmarks to evaluate the performance of existing, improved and modified evolutionary algorithms. In this paper, we propose a new hybrid method, namely SIWO, by embedding space transformation search (STS) into invasive weed optimization to solve complex fixed-point problems. Invasive weed optimization suffers from premature convergence when solving complex optimization problems. Using STS transforms the current search space into a new search space by simultaneously evaluating solutions in the current and transformed spaces. This increases the probability that a solution is closer to the global optimum. Therefore, we can avoid premature convergence and the convergence speed is also increased. To evaluate the performance of SIWO, four complex fixed-point problems are chosen from the literature. Our findings demonstrate that SIWO can solve complex fixed-point problems with great precision. Moreover, the numerical results demonstrate that SIWO is an effective and efficient algorithm compared with some state-of-the-art algorithms.
机译：现实生活中的问题被用作评估现有，改进和修改的进化算法的性能的基准。在本文中，我们提出了一种新的混合方法，即Siwo，通过将空间转换搜索（STS）嵌入到侵入性杂草优化来解决复杂的定点问题。侵入杂草优化在解决复杂优化问题时遭受过早的收敛性。使用STS将当前搜索空间转换为新的搜索空间，通过同时评估当前和转换空间中的解决方案。这增加了解决方案更接近全局最佳的可能性。因此，我们可以避免过早收敛，收敛速度也增加。为了评估Siwo的性能，从文献中选择了四个复杂的定点问题。我们的研究结果表明，Siwo可以以极大的精度解决复杂的定点问题。此外，数值结果表明，与一些最先进的算法相比，SiWO是一种有效且有效的算法。

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