10 papers
Learning volatility-adaptive forgetting via GARCH-modulated LSTM for stock price forecasting
Xin-Rui Lu, Da-Qing Zhang
Stock price forecasting is hindered by the heteroscedastic nature of financial time series, in which turbulent and tranquil regimes alternate. Although the Long Short-Term Memory (…
A decomposition-integration framework coupling singular spectrum analysis with a volatility-adaptive LSTM for stock price forecasting
Xin-Rui Lu, Da-Qing Zhang
Financial time series exhibit multi-scale, high-noise, and non-stationary volatility dynamics. Decomposition--integration frameworks built on complete ensemble empirical mode decom…
Adaptive regularization parameter selection for high-dimensional inverse problems: A Bayesian approach with Tucker low-rank constraints
Qing-Mei Yang, Da-Qing Zhang
This paper introduces a novel variational Bayesian method that integrates Tucker decomposition for efficient high-dimensional inverse problem solving. The method reduces computatio…
GARCH-FIS: A Hybrid Forecasting Model with Dynamic Volatility-Driven Parameter Adaptation
Wen-Jing Li, Da-Qing Zhang
This paper proposes a novel hybrid model, termed GARCH-FIS, for recursive rolling multi-step forecasting of financial time series. It integrates a Fuzzy Inference System (FIS) with…
Orthogonal Subspace Clustering: Enhancing High-Dimensional Data Analysis through Adaptive Dimensionality Reduction and Efficient Clustering
Qing-Yuan Wen, Da-Qing Zhang
This paper presents Orthogonal Subspace Clustering (OSC), an innovative method for high-dimensional data clustering. We first establish a theoretical theorem proving that high-dime…
Enhanced Prediction Model for Time Series Characterized by GARCH via Interval Type-2 Fuzzy Inference System
Hongpei Shao, Da-Qing Zhang, Feilong Lu
GARCH-type time series (characterized by Generalized Autoregressive Conditional Heteroskedasticity) exhibit pronounced volatility, autocorrelation, and heteroskedasticity. To addre…
Edge Detection based on Channel Attention and Inter-region Independence Test
Ru-yu Yan, Da-Qing Zhang
Existing edge detection methods often suffer from noise amplification and excessive retention of non-salient details, limiting their applicability in high-precision industrial scen…
Edge-preserving Image Denoising via Multi-scale Adaptive Statistical Independence Testing
Ruyu Yan, Da-Qing Zhang
Edge detection is crucial in image processing, but existing methods often produce overly detailed edge maps, affecting clarity. Fixed-window statistical testing faces issues like s…
A Study on Group Decision Making Problem Based on Fuzzy Reasoning and Bayesian Networks
Shui-jin Rong, Wei Guo, Da-qing Zhang
Aiming at the group decision - making problem with multi - objective attributes, this study proposes a group decision - making system that integrates fuzzy inference and Bayesian n…
Orthogonal Factor-Based Biclustering Algorithm (BCBOF) for High-Dimensional Data and Its Application in Stock Trend Prediction
Yan Huang, Da-Qing Zhang
Biclustering is an effective technique in data mining and pattern recognition. Biclustering algorithms based on traditional clustering face two fundamental limitations when process…