THE APPLICATION OF STANDARD GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (SGARCH) MODEL IN FORECASTING THE STOCK PRICE OF BARITO PACIFIC by Edwin Setiawan Nugraha, Celine Alvina

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CRYPTOCURRENCY PRICE PREDICTION: A HYBRID LONG SHORT-TERM MEMORY MODEL WITH GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY by Indah Manfaati Nur, Rifqi Nugrahanto, Fatkhurokhman Fauzi

“…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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Assessing Expected Shortfall in Risk Analysis Through Generalized Autoregressive Conditional Heteroskedasticity Modeling and the Application of the Gumbel Distribution by Bingjie Wang, Yihui Zhang, Jia Li, Tao Liu

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Generalized Autoregressive Conditional Heteroskedastic Model to Examine Silver Price Volatility and Its Macroeconomic Determinant in Ethiopia Market by Amare Wubishet Ayele, Emmanuel Gabreyohannes, Hayimro Edmealem

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Comparison of the Symmetric and Asymmetric Generalized Autoregressive Conditional Heteroscedasticity (GARCH) Models in Forecasting the 2018-2023 Jakarta Composite Index by Yenni Angraini, Adelia Putri Pangestika, I Made Sumertajaya

“…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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The Influence of Meteorological Conditions and Seasons on Surface Ozone in Chonburi, Thailand by Sawaeng Kawichai, Wissanupong Kliengchuay, Htoo Wai Aung, Sarima Niampradit, Rachaneekorn Mingkhwan, Talisa Niemmanee, Wechapraan Srimanus, Walaiporn Phonphan, San Suwanmanee, Kraichat Tantrakarnapa

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Direct Conditional Score Modeling for Accelerated MRI Reconstruction by Hongki Lim

“…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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Managing the Risk via the Chi-Squared Distribution in VaR and CVaR with the Use in Generalized Autoregressive Conditional Heteroskedasticity Model by Fazlollah Soleymani, Qiang Ma, Tao Liu

“…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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A General On-Orbit Absolute Radiometric Calibration Method Compatible with Multiple Imaging Conditions by Liming Fan, Zhongjin Jiang, Shuhai Yu, Yunhe Liu, Dong Wang, Maosheng Chen

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Using Transformers and Reinforcement Learning for the Team Orienteering Problem Under Dynamic Conditions by Antoni Guerrero, Marc Escoto, Majsa Ammouriova, Yangchongyi Men, Angel A. Juan

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A new neurodynamic model with Adam optimization method for solving generalized eigenvalue problem by Ebrahim Ganjalipour, Khadijeh Nemati, Amir Hosein Refahi Sheikhani, Hashem Saberi Najafi

“…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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Reconstruction of cosmological models are inspired by generalization of the Chaplygin gas by П.Ю. Цыба, О.В. Разина, Н.Т. Суйкимбаева

“… 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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Defi-crime: condition, trends and criminological models by E. L. Sidorenko

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The Model of Fundamental Chemical Training of Bachelors of Technical and Technological Directions in the Conditions of Blended Learning by N. M. Vostrikova

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The Influence of Magnetohydrodynamic Flow and Slip Condition on Generalized Burgers’ Fluid with Fractional Derivative by Nassief et al.

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Viscoelastic Response of Sugar Beet Root Tissue in Quasi-Static and Impact Loading Conditions by Paweł Kołodziej, Krzysztof Gołacki, Zbigniew Stropek

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Accurate Conditional Variance Models for Predicting Asymmetric Volatility in Cryptocurrency Markets by Onur Çelebi, Erhan Demireli

“…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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SHSRD: Efficient Conditional Diffusion Model for Single Hyperspectral Image Superresolution by Song Yan, Min Li, Yujie He, Yao Gou, Yusen Zhang

“…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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A CVAE-based generative model for generalized B1 inhomogeneity corrected chemical exchange saturation transfer MRI at 5 T by Ruifen Zhang, Qiyang Zhang, Yin Wu

“…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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INTERLAMINAR STRESS ANALYSIS OF INCOMPATIBLE GENERALIZED MIXED ELEMENT MODEL FOR COMPOSITE LAMINATES WITH A HOLE by QING Guanghui, WANG Yonggang, WANG Xie

“…In order to investigate the stress concentration phenomenon and analyze the distribution characteristics of the interlaminar stress in the hole edge region of composite laminates. Based on the generalized mixed variational principle, the generalized mixed finite element model for laminated plates with various stacking modes were established. …”
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