Results 21 to 30 of about 13,877 (197)

Predicting Solar Photovoltaic Power Output in Saudi Arabia's Jazan Region: Performance Comparison of Machine Learning Models

Energy Science &Engineering, EarlyView.
Workflow of the PV power estimation and ML forecasting methodology. ABSTRACT Accurate prediction of solar panel energy output is vital for managing power systems effectively and maintaining a stable electrical grid. This is especially important in regions that rely heavily on renewable sources. This research provides a direct comparison of five machine
Abdoalateef Alzhrani, Abdullahi Abubakar Mas'ud, Mohd Khairul Amri Kamarudin, Firdaus Muhammad‐Sukki, Abdullahi Mohammad   +4 more
wiley   +1 more source

High Precision Prediction Model of Wind Speed for Underground Mine Tunnel by Using ASTF Net

Energy Science &Engineering, EarlyView.
This paper proposes an Adaptive Spectral‐Temporal Fusion Net (ASTF‐Net), which features a novel decomposition‐ensemble framework with adaptive feature fusion. This design deliberately balances spectral and temporal features and effectively boosts prediction accuracy in complex ventilation environments. ABSTRACT An Adaptive Spectral‐Temporal Fusion Net (
Ruo‐Qi Li, Yong‐Qiang Chai, Lian Shi, Fu‐Gang Wang, Mi Liu   +4 more
wiley   +1 more source

Environmental Control for Edible Fungi Cultivation Based on Temporal Information and Deep Learning

Food Bioengineering, EarlyView.
ABSTRACT Currently, there are still prevalent issues in greenhouse environmental regulation, such as response lag, low control accuracy, and difficulty in coping with sudden environmental disturbances. To achieve high‐precision and dynamic control of the edible fungi cultivation environment, this study proposes an edible fungi environmental control ...
Xiangyan Wang, Shuangcheng Huang, Qingbo Lu, Xinyi Guo   +3 more
wiley   +1 more source

Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models

Journal of Forecasting, EarlyView.
ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly, Pooja Sengupta, Divya Aggarwal   +2 more
wiley   +1 more source

A Novel Text‐Based Framework for Forecasting Carbon Prices

Journal of Forecasting, EarlyView.
ABSTRACT This study proposes a text‐based framework for predicting EU carbon prices. Using weekly data from 2020 to 2024, we construct a multivariate dataset combining financial indicators, commodity prices, Google Trends measures, and news‐based sentiment extracted using FinBERT.
Christian Oliver Ewald, Yaoyu Li
wiley   +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

A Reassessment of Petrochemistry of ~1.2 Ga Tonalitic Rocks of the Northern Tugela Terrane, Natal Metamorphic Belt, South Africa: Further Constraints on the Evolution of This Belt

Geological Journal, EarlyView.
Our petrochemical studies on ~1.2 Ga granitoids of the Natal Metamorphic Belt, South Africa, do not suggest any property similar to Phanerozoic‐style subduction‐related granitoids. Plot of Kotongweni Tonalite in Y versus Sr diagram (after Moyen 2011), note that most samples have Sr/Y < 50.
Palesa Leuta, Saumitra Misra, Thembiso O. Basupi   +2 more
wiley   +1 more source

Impact of China's National Volume‐Based Procurement Policy on Cost, Volume, and Market Structure: An Interrupted Time‐Series Analysis of Montelukast Sodium

Health Care Science, EarlyView.
Using ARIMA‐based interrupted time‐series analysis, this study reveals that China's NVBP policy significantly reduced daily costs and enhanced affordability, driving generic substitution and the elimination of low‐quality products. Additionally, non‐winning manufacturers adopted strategic pricing behaviors to segment the market.
Yufei Cheng, Fanyu Liu, Yongyi Wu, Siyu Liu, Xiaohan Fan, Bin Jiang, Zhao Yang   +6 more
wiley   +1 more source

Household Consumption Intentions by Income Group During Monetary Policy Easing and Tightening

International Journal of Finance &Economics, EarlyView.
ABSTRACT We investigate how the monetary policy interest rate affects Brazilian households' consumption intentions under two distinct regimes: monetary easing and tightening cycles. Using data from low‐ and high‐income households, we assess both the magnitude and the dynamics of this relationship.
Helder Ferreira de Mendonça, Daniel Pereira dos Anjos   +1 more
wiley   +1 more source

Risk Forecasting in Shipping Exchange‐Traded‐Fund (ETF) Markets

International Journal of Finance &Economics, EarlyView.
ABSTRACT This article examines the risk properties of freight‐derivative‐based exchange‐traded funds (ETFs), focusing on the Breakwave Dry Bulk Shipping ETF (BDRY), and evaluates the accuracy of Value‐at‐Risk (VaR) and Expected Shortfall (ES) forecasts across a range of econometric models.
Christos Katris, Manolis G. Kavussanos, Stergiani (Stella) A. Moysiadou   +2 more
wiley   +1 more source