Results 221 to 230 of about 143,911 (316)

Hybrid fuzzy clustering and temporal deep learning framework for multi-parameter forecasting in industrial thermal processes. [PDF]

Front Artif Intell
Vignesh V, Narendran GV, Senthil Kumar R, Sitharthan R.   +3 more
europepmc   +1 more source

Beta Forecasting With Realized Beta Estimators and Machine Learning Algorithms

Journal of Forecasting, EarlyView.
ABSTRACT This paper applies machine learning algorithms to the modeling of realized betas for the purposes of forecasting stock systematic risk. Higher levels of beta forecast accuracy are demonstrated, relative to other studies in the literature. These improvements are also highly significant, both statistically and economically.
Bao Doan, Dulani Jayasuriya, John B. Lee, Jonathan J. Reeves   +3 more
wiley   +1 more source

Deep learning architectures for EEG-based classification of Dravet syndrome: A comparative study of pre-trained and non-pretrained hybrid CNN-LSTM models. [PDF]

PLoS One
Hussain S, Jawed S, Mir A, Ibrahim Ali M, Al-Baradie R, Alaqili N, Nassim Ali EM, Bashir S.   +7 more
europepmc   +1 more source

Temporal Robustness in Cross‐Country Gross Domestic Product Forecasting: Evidence From Classical, Regime‐Switching, and Ensemble Models

Journal of Forecasting, EarlyView.
ABSTRACT This study evaluates whether the relative performance of gross domestic product forecasting models is temporally robust across economies and changing macroeconomic conditions. Using annual real gross domestic product data from the World Bank for 177 separately reported economies and territories, we conduct a common‐vintage pseudo‐out‐of‐sample
Achilleas Tampouris, Chaido Dritsaki
wiley   +1 more source

Predicting influenza in the post-COVID era: assessing LSTM, GRU, and transformer robustness to covariate shift. [PDF]

Front Artif Intell
Din ANA, Woldegerima WA, Wu J.
europepmc   +1 more source

LSTM-Based Forecasting of Value at Risk and Expected Shortfall: A Comparison with Classical Approaches

reservedThis thesis compares traditional econometric models and deep learning methods for forecasting market risk, with a focus on Value-at-Risk (VaR) and Expected Shortfall (ES).
DIAN, KAOUTHAR
core  

From Temperature Fluctuations to Precise Control: Biochemical Techniques Integrated Digital‐Intelligent Technology for Vegetable Preservation

Future Postharvest and Food, EarlyView.
The physiological effects and molecular responses of postharvest vegetables to temperature fluctuations, and multi‐technology integration strategies for maintaining postharvest vegetable quality. ABSTRACT Vegetables are indispensable agricultural products in the human diet. With the continuous growth of vegetable production and consumption, postharvest
Shuaishuai Dai, Kuo Chen, Xing Xing, Liqun Ma, Hongliang Zhu   +4 more
wiley   +1 more source

A Hybrid Ridge Regression-Convolutional Bidirectional Long Short-Term Memory Framework with Dual-Level Transfer Learning for State-of-Health Estimation of Lithium-Ion Batteries Under High Temperatures. [PDF]

Materials (Basel)
Ge C, Wu C, Zhang Z, Cao K, Wang L, Gao M, He X.   +6 more
europepmc   +1 more source

The Global Patent Landscape of Mushroom‐Derived Functional Foods: Current Status, Future Perspectives, and Artificial Intelligence–Driven Exploration

Food Safety and Health, EarlyView.
The global patent landscape of mushroom‐derived functional food was widely analyzed, and AI‐integrated approaches realizing cost‐effective and reliable exploration of functional foods derived from mushrooms were explored. ABSTRACT Global health concerns and the increasing demand for nourishment have collectively driven the rising demand for functional ...
Xihong Zhao, Linhuizi Xiang, Dongmei Liu, Shoucheng Qin, Yue Chen, Xueyan Sun   +5 more
wiley   +1 more source

CTGAN-Based Data Augmentation and XGBoost-LSTM Strength Prediction of CSG. [PDF]

Materials (Basel)
Li G, Zhang Y, Tian Q, Guo L, Chai Q.
europepmc   +1 more source