Results 111 to 120 of about 276,034 (269)
Research on Oil Well Production Prediction Based on GRU-KAN Model Optimized by PSO
EnergiesAccurately predicting oil well production volume is of great significance in oilfield production. To overcome the shortcomings in the current study of oil well production prediction, we propose a hybrid model (GRU-KAN) with the gated recurrent unit (GRU)
Bo Qiu +5 more
semanticscholar +1 more source
Breeding 5.0: Artificial intelligence (AI)‐decoded germplasm for accelerated crop innovation
Journal of Integrative Plant Biology, EarlyView.ABSTRACT Crop breeding technologies are vital for global food security. While traditional methods have improved yield, stress tolerance, and nutrition, rising challenges such as climate instability, land loss, and pest pressure now demand new solutions.
Jiayi Fu +4 more
wiley +1 more source
COMPARATIVE EVALUATION OF ARIMA AND GRU MODELS IN PREDICTING RUPIAH DOLLAR EXCHANGE RATE
Media StatistikaThis study evaluates the effectiveness of the ARIMA (Autoregressive Integrated Moving Average) and GRU (Gated Recurrent Unit) models in forecasting the USD–Rupiah exchange rate.
Dwi Fitrianti +4 more
doaj +1 more source
Advanced Short-Term Load Forecasting with XGBoost-RF Feature Selection and CNN-GRU
ProcessesAccurate and efficient short-term load forecasting (STLF) is essential for optimizing power system operations. This study proposes a novel hybrid forecasting model that integrates XGBoost-RF feature selection with a CNN-GRU neural network to enhance ...
Jingping Cui +6 more
semanticscholar +1 more source
Financial Time Series Uncertainty: A Review of Probabilistic AI Applications
Journal of Economic Surveys, EarlyView.ABSTRACT Probabilistic machine learning models offer a distinct advantage over traditional deterministic approaches by quantifying both epistemic uncertainty (stemming from limited data or model knowledge) and aleatoric uncertainty (due to inherent randomness in the data), along with full distributional forecasts.
Sivert Eggen +4 more
wiley +1 more source
FGFR1OP2-FGFR1 induced myeloid leukemia and T-cell lymphoma in a mouse model
Haematologica, 2016 Haiyan Qin +3 more
doaj +1 more source
An Overview of Deep Learning Techniques for Big Data IoT Applications
International Journal of Communication Systems, Volume 39, Issue 4, 10 March 2026.Reviews deep learning integration with cloud, fog, and edge computing in IoT architectures. Examines model suitability across IoT applications, key challenges, and emerging trends Provides a comparative analysis to guide future deep learning research in IoT environments.
Gagandeep Kaur +2 more
wiley +1 more source
COMPARISON OF ARIMA, LSTM, AND GRU MODELS FOR FORECASTING SALES OF HIT AEROSOL PRODUCTS
Pilar Nusa MandiriA more accurate forecasting model, such as LSTM, can significantly enhance business efficiency by providing more reliable predictions of future sales, allowing for better inventory management, optimized production schedules, and more precise distribution
Nendi Sunendar, Yan Rianto
doaj +1 more source
Battery Energy, Volume 5, Issue 2, March 2026.SOC estimation is performed using a newly developed online HFF‐GRU method. Improves charge balancing among battery cells, leading to a substantial increase in the battery pack's lifespan. ABSTRACT Accurate estimation of state of charge (SoC) and maintaining balanced charge levels across secondary battery cells are crucial in battery management systems (
Md Ohirul Qays +4 more
wiley +1 more source