Transient Detection Modeling as Imbalance Data Classification

Transient Detection Modeling as Imbalance Data Classification
复制标题

DOI:
10.1109/ickii.2018.8569123
复制
发表时间:
2018-07
期刊:
2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)
影响因子:
--
通讯作者:
Aireen B. Tabacolde;Tossapon Boongoen;Natthakan Iam-on;J. Mullaney;U. Sawangwit;K. Ulaczyk
Aireen B. Tabacolde;Tossapon Boongoen;Natthakan Iam-on;J. Mullaney;U. Sawangwit;K. Ulaczyk
中科院分区:
其他
文献类型:
--
作者:
Aireen B. Tabacolde;Tossapon Boongoen;Natthakan Iam-on;J. Mullaney;U. Sawangwit;K. Ulaczyk

文献摘要

相似文献

大量天文数据的获取促使天文学家加入大数据科学和人工智能的全球趋势。引力波光学瞬态观测器是捕捉瞬态事件的视觉对应物,提供数百万个观测源,然后参考模拟数据系统地处理和分析,以识别真实的源。基本上,这项研究的重点是利用传统的数据挖掘应用程序。
Acquisition of large astronomical data prompted astronomers to join the global trend of big data science and artificial intelligence. The Gravitational-wave Optical Transient Observers is a visual counterpart in capturing transient events provides millions of observed sources which are then systematically process and analyze in reference to simulated data in order to identify real sources. Basically, this study focuses in utilizing conventional data mining applications.