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Python多核并行计算在海量星表交叉证认中的应用
  • 期刊名称：《中国科学》G辑
  • 时间：0
  • 页码：102-107
  • 语言：中文
  • 相关项目：利用数据挖掘技术确定类星体候选体
作者： 赵永恒|彭南博|张彦霞|裴彤|
同期刊论文项目
利用数据挖掘技术确定类星体候选体
期刊论文 38 会议论文 2
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Discrimination Between Quasars and Stars by Support Vector Machines
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聚类算法在天文学中的应用
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An automated algorithm for determining photometric redshifts of quasars
A simple and effective algorithm for quasar candidate selection
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Automated Classification of Quasars and Stars
Separating quasars from stars by support vector machines
A high efficient and fast kNN algorithm based on CUDA
Comparison of several algorithms for celestial object classification
Exploration of SDSS stellar database by AutoClass
Overview of photometric redshift estimators
System architectural design of multiwavelength data mining
Predicting photometric redshifts with polynomial regression
The Design and Development of Large-Scale Catalogue Federation System (XMaS_VO)
Support vector machines and kd-tree for separating quasars from large survey data bases
Two Novel Approaches for Photometric Redshift Estimation based on SDSS and 2MASS
Radio Star Candidates from FIRST and 2MASS Databases
Knowledge discovery in astronomical data
Discrimination of Point Sources Using Radial Basis Function Network and Random Forest
The Application of kd-tree in Astronomy
Feedback of Active Galactic Nuclei in Seyfert 2 Galaxies
An automatic system for photometric redshift estimation based on sky survey data
Estimating Photometric Redshifts of Quasars Using Support Vector Machines
k-Nearest Neighbors for automated classification of celestial objects
Random forest algorithm for classification of multiwavelength data
基于稀疏表示的谱线自动提取方法
Morphology classification and photometric redshift measurement of galaxies
中国虚拟天文台交叉证认工具的开发和应用
测光红移算法概述
海量星表融合系统（XMaS_VO）的设计与开发