Výsledky vyhledávání - "Shin, Jungmin"

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The R package psvmSDR: A Unified Algorithm for Sufficient Dimension Reduction via Principal Machines

Autor: Shin, Jungmin, Shin, Seung Jun, Artemiou, Andreas

Sufficient dimension reduction (SDR), which seeks a lower-dimensional subspace of the predictors containing regression or classification information has been popular in a machine learning community. In this work, we present a new R software package p

Externí odkaz: http://arxiv.org/abs/2409.01547

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Extreme Solar Flare Prediction Using Residual Networks with HMI Magnetograms and Intensitygrams

Autor: Yun, Juyoung, Shin, Jungmin

Solar flares, especially C, M, and X class, pose significant risks to satellite operations, communication systems, and power grids. We present a novel approach for predicting extreme solar flares using HMI intensitygrams and magnetograms. By detectin

Externí odkaz: http://arxiv.org/abs/2405.14750

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Analysis and Predictive Modeling of Solar Coronal Holes Using Computer Vision and ARIMA-LSTM Networks

Autor: Yun, Juyoung, Shin, Jungmin

In the era of space exploration, coronal holes on the sun play a significant role due to their impact on satellites and aircraft through their open magnetic fields and increased solar wind emissions. This study employs computer vision techniques to d

Externí odkaz: http://arxiv.org/abs/2405.09802

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A least distance estimator for a multivariate regression model using deep neural networks

Autor: Shin, Jungmin, Shin, Seung Jun, Bang, Sungwan

We propose a deep neural network (DNN) based least distance (LD) estimator (DNN-LD) for a multivariate regression problem, addressing the limitations of the conventional methods. Due to the flexibility of a DNN structure, both linear and nonlinear co

Externí odkaz: http://arxiv.org/abs/2401.03123

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Data transform composition for efficient information integration

Autor: Shin, Jungmin.

Publikováno v: RESTRICTED TO UF STUDENTS, STAFF, FACULTY AND ON-CAMPUS USE UNTIL 2010-02-28

Thesis (Ph. D.)--University of Florida, 2009.
Title from title page of source document. Document formatted into pages; contains 72 pages. Includes vita. Includes bibliographical references.

Externí odkaz: http://purl.fcla.edu/fcla/etd/UFE0024907

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