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Comparison of the Symmetric and Asymmetric Generalized Autoregressive Conditional Heteroscedasticity (GARCH) Models in Forecasting the 2018-2023 Jakarta Composite Index
Published 2024-05-01“…The research aimed to compare the accuracy of the symmetric ARCH/ Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and asymmetric TGARCH models in forecasting weekly Jakarta Composite Index (JCI) data on January 1st, 2018, to April 24th, 2023, by involving the influence of COVID-19 as a covariate variable and applying several validation scenario models to training and testing data. …”
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CRYPTOCURRENCY PRICE PREDICTION: A HYBRID LONG SHORT-TERM MEMORY MODEL WITH GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY
Published 2023-09-01“…To overcome this volatility factor, this research used the Generalized Autoregressive Conditional Heteroscedasticity forecasting method to describe the heteroscedasticity factor, as well as a Recurrent Neural Network (RNN) with long-short-term memory that has feedback in modeling sequential data for time series analysis. …”
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Direct Conditional Score Modeling for Accelerated MRI Reconstruction
Published 2024-01-01“…This paper presents a novel approach called Direct Conditional Score (DCS) modeling that directly models the conditional score function, eliminating the need for separate likelihood terms. …”
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Reconstruction of cosmological models are inspired by generalization of the Chaplygin gas
Published 2022-03-01“… This paper considers models arising from the composition of the modified Gauss–Bonnet gravity (the Gauss–Bonnet invariant) and the general relativity (the Ricci scalar) against the background of a flat, homogeneous, and isotropic space-time described by the Friedmann–Robertson–Walker metric. …”
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Managing the Risk via the Chi-Squared Distribution in VaR and CVaR with the Use in Generalized Autoregressive Conditional Heteroskedasticity Model
Published 2025-04-01“…This paper develops a framework for quantifying risk by integrating analytical derivations of Value at Risk (VaR) and Conditional VaR (CVaR) under the chi-squared distribution with empirical modeling via Generalized Autoregressive Conditional Heteroskedasticity (GARCH) processes. …”
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The Influence of Meteorological Conditions and Seasons on Surface Ozone in Chonburi, Thailand
Published 2025-03-01Get full text
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Accurate Conditional Variance Models for Predicting Asymmetric Volatility in Cryptocurrency Markets
Published 2024-12-01“…This study includes tests on the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model and its derivatives to conduct complex and detailed volatility analysis for the 5 highest-volume cryptocurrencies traded in September 2023. …”
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A General On-Orbit Absolute Radiometric Calibration Method Compatible with Multiple Imaging Conditions
Published 2024-09-01Subjects: Get full text
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A new neurodynamic model with Adam optimization method for solving generalized eigenvalue problem
Published 2021-06-01“…In this paper we proposed a new neurodynamic model with recurrent learning process for solving ill-condition Generalized eigenvalue problem (GEP) Ax = lambda Bx. our method is based on recurrent neural networks with customized energy function for finding smallest (largest) or all eigenpairs. …”
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Reduced-Order Models and Conditional Expectation: Analysing Parametric Low-Order Approximations
Published 2025-02-01“…This last case is taken as the “Leitmotiv” for the following discussion.A reduced-order model is produced from the full-order model through some kind of projection onto a relatively low-dimensional manifold or subspace. …”
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Using Transformers and Reinforcement Learning for the Team Orienteering Problem Under Dynamic Conditions
Published 2025-07-01Subjects: Get full text
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SHSRD: Efficient Conditional Diffusion Model for Single Hyperspectral Image Superresolution
Published 2025-01-01“…To better solve the above-mentioned problems from the perspective of dataset, we propose SHSRD, an advanced superresolution framework specifically designed for HSIs based on diffusion model. It incorporates a spectral information injection module, which selectively introduces diverse spectral information into the model in a conditional manner, thereby enabling efficient spectral information perception. …”
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MODELS OF INCREASING THE COMPETITIVENESS OF ORGANIZATIONS IN THE CONDITIONS OF SHERING ECONOMY
Published 2022-02-01“…The features of groups of business models of the sharing economy are generalized. The models of increasing the competitiveness of organizations in the conditions of the sharing economy, which are determined by the existing business models of the sharing economy, are determined.…”
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A CVAE-based generative model for generalized B1 inhomogeneity corrected chemical exchange saturation transfer MRI at 5 T
Published 2025-05-01“…The recently proposed supervised deep learning approach reconstructed B1 inhomogeneity corrected CEST effect at the identical B1 as of the training data, hindering its generalization to other B1 levels. In this study, we proposed a Conditional Variational Autoencoder (CVAE)-based generative model to generate B1 inhomogeneity corrected Z spectra from single CEST acquisition. …”
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