• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>IEEE Symposium Series on Computational Intelligence >A Novel Exoplanetary Habitability Score via Particle Swarm Optimization of CES Production Functions
【24h】

A Novel Exoplanetary Habitability Score via Particle Swarm Optimization of CES Production Functions

机译：基于粒子群优化的CES生产函数的新的系外行星宜居性评分

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

摘要

The search for life has two goals essentially: looking for planets with Earth-like conditions (Earth similarity) and looking for the possibility of life in some form (habitability). Determining habitability from exoplanet data requires that determining parameters are collectively considered before coming up with a conclusion as no single factor alone contributes to it. Our proposed models, would serve as an indicator while looking for new habitable worlds, if computed with precision and efficiency. The models are of the type constrained optimization, multivariate, convex but may suffer from curvature violation and premature convergence impacting desired habitability scores. We mitigate the problem by proposing modified Particle Swarm optimization (PSO) to tackle constraints and ensuring global optima. In the process, a python library to tackle such problems has been created.
机译：寻找生命本质上有两个目标：寻找具有类似地球条件的行星（地球相似性）和寻找某种形式的生命的可能性（可居住性）。从系外行星数据确定可居住性要求在得出结论之前要综合考虑确定参数，因为没有单独的因素会对其做出贡献。如果精确且高效地计算，我们提出的模型将在寻找新的可居住世界时作为指标。这些模型具有约束优化，多元，凸型的类型，但可能会受到曲率违规和过早收敛的影响，从而影响所需的可居住性得分。我们通过提出改进的粒子群优化（PSO）来解决约束并确保全局最优，从而缓解了这一问题。在此过程中，创建了一个Python库来解决此类问题。

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