Results 1 to 10 of about 643 (115)

Preferential trading in agriculture: New insights from a structural gravity analysis and machine learning

American Journal of Agricultural Economics, EarlyView.
Abstract Preferential trade agreements (PTAs) contain various non‐tariff provisions, yet identifying their trade effects remains challenging because these commitments are high‐dimensional and strongly correlated within agreements. We estimated a theory‐consistent structural gravity model with domestic flows for 26 agricultural subsectors over 1988–2017
Dongin Kim, Sandro Steinbach
wiley   +1 more source

Performance improvement of discrete‐time linear‐quadratic regulators applied to uncertain linear systems using the Tikhonov regularization method

Asian Journal of Control, EarlyView.
Abstract The linear‐quadratic regulator (LQR) problem of optimal control of an uncertain discrete‐time linear system (DTLS) is revisited in this paper from the perspective of Tikhonov regularization. We show that an optimally chosen regularization parameter reduces, compared to the classical LQR, the values of a scalar error function, as well as the ...
Fernando Pazos, Amit Bhaya
wiley   +1 more source

From Informality to Green Development: How the Shadow Economy Affects Green Finance, Green Innovation, and Green Trade

Business Strategy and the Environment, EarlyView.
ABSTRACT Achieving green transition has become an essential policy priority for which economies need to mobilize green finance, increase green innovation, and promote trade in environmentally sustainable goods and services. However, the effectiveness of policies for enhanced green development depends not only on their design but also on their ...
Sami Ur Rahman, Muhammad Ibrahim Khan, Javed Hussain, Imran Ali Khan   +3 more
wiley   +1 more source

Evaluating Regularization Estimators Under Severe Multicollinearity: A Simulation and Empirical Study on Housing Prices

Mathematical and Computational Applications
Accurate housing price prediction is important for market efficiency and purchasing decisions. However, multicollinearity among independent variables remains a major challenge in linear regression, causing variance inflation and reducing the reliability ...
Osman Ufuk Ekiz, Meltem Ekiz
doaj   +1 more source

Subperiosteal tunnel assisted graft (STAG) technique: Report of two cases

Clinical Advances in Periodontics, EarlyView.
Abstract Background This case report describes the clinical application of the subperiosteal tunnel‐assisted graft (STAG) technique, a novel approach for peri‐implant phenotype modification and keratinized tissue augmentation. Although free gingival grafts remain the gold standard for increasing keratinized tissue width, their effectiveness may be ...
Seiko Min
wiley   +1 more source

Machine Learning‐Assisted Design of BaTiO3‐Based Superparaelectric High‐Entropy Ceramics with Superior Energy Storage

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
This study employed an adaptive iterative strategy combining machine learning algorithms, domain knowledge, experimental design, and experimental feedback to aim to precisely and quickly discover high‐entropy ceramics with excellent energy storage performance.
Haowen Liu, Xiaoyan Zhang, Zhiyuan Ma, Kailong Ma, Xiwei Qi   +4 more
wiley   +1 more source

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

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

AFSR: An Adaptive Factor Score Regression Framework for High-Dimensional Correlation Matrix Estimation

Journal of Mathematics
The accurate estimation of correlation matrices is a foundational challenge in high-dimensional statistics. The sample correlation matrix, while unbiased, suffers from high variance when the number of variables p is large relative to the sample size n ...
Muath Awadalla, Yücel Tandoğdu
doaj   +1 more source

A New Implementation of Network GARCH Model for Stock Volatility and Co‐Volatility Forecasting

Journal of Forecasting, EarlyView.
ABSTRACT Volatility clustering and spillovers are key features of financial time series with many cross‐sectional assets. While network analysis links similar or correlated stocks and helps trace volatility spillovers, contemporary multivariate ARCH‐GARCH formulations struggle to represent structured network dependence and remain parsimonious.
Peiyi Zhou
wiley   +1 more source