J-PLUS. Support vector regression

B2FIND2026-04-11 收录

恒星参数预测

支持向量回归

数据链接：

https://b2find.eudat.eu/dataset/d25a70b2-4835-59f7-84eb-35c0d843a9bb 数据链接链接失效反馈

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Stellar parameters are among the most important characteristics in studies of stars, which are based on atmosphere models in traditional methods. However, time cost and...

SPLUS DR4 VAC - Predicted Parameters

天文学

恒星参数预测

VizieR online Data Catalogue associated with article published in journal Astronomy and Astrophysics with title ' Stellar atmospheric parameters and chemical abundances of ~5 million stars from S-PLUS

DataCite Commons2025-03-03 更新160

Prediction of Coal Calorific Value Based on Coal Quality-Derived Indicators and Support Vector Regression

煤炭热值预测

支持向量回归

本研究解决了传统煤炭热值预测模型主要依赖线性回归和单源近端分析数据的局限性。基于465份中国煤炭样品，结合近似分析、极限分析，构建衍生指标（可燃物含量-CC、碳氢指数-CHI、可燃物碳-CIC），提出一种结合平均影响值（MIV）特征选择和支持向量回归（SVR）的非线性建模方法。结果表明，推导指标与净热值（NCV）之间的皮尔逊相关系数均超过0.93，优于原始项目。以CC-CHI-CIC-FCad为特

DataCite Commons2025-10-18 更新90

SPLUS DR4 VAC - Predicted Parameters

恒星参数预测

银河系天文学

The APOGEE, GALAH, and LAMOST spectroscopic surveys have substantially contributed to our understanding of the Milky Way by providing a wide range of stellar parameters and...

B2FIND50

Results of the Recursive Feature Elimination (RFE) of the support vector regression.

支持向量回归

递归特征消除

Results of the Recursive Feature Elimination (RFE) of the support vector regression.

NIAID Data Ecosystem90

Stellar parameters for ~650000 stars with APOGEE

恒星参数预测

恒星光谱深度学习

We train a convolutional neural network, APOGEE Net, to predict Teff, logg, and, for some stars, [Fe/H], based on the APOGEE spectra. This is the first pipeline adapted for...

B2FIND60

J-PLUS. Support vector regression

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