Results 141 to 150 of about 5,352,065 (277)

Machine Learning Modeling of Drill Cuttings Transport Based on Computational Fluid Dynamics Simulation Data

Energy Science &Engineering, EarlyView.
Machine learning surrogates accurately predict drill cuttings transport from computational fluid dynamics data, with Reynolds number dominating system behavior. While tree‐based models excel in accuracy, Gaussian process regression provides physically consistent, smooth predictions essential for reliable drilling simulations.
Kathrin Skinder, Mostafa M. Abdelhafiz, Khizar Shahid, Gunther Brenner   +3 more
wiley   +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

Adaptive-projection intrinsically transformed multivariate empirical mode decomposition in cooperative brain-computer interface applications. [PDF]

Philos Trans A Math Phys Eng Sci, 2016
Hemakom A, Goverdovsky V, Looney D, Mandic DP.   +3 more
europepmc   +1 more source

Hybrid Approach of an Empirical Mode Decomposition and Wavelet Support Vector Machine for Forecasting Singapore Tourist Arrivals to Malaysia

, 2018
Time series modelling and forecasting has fundamental importance to various practical domains. Thus, a lot of active research works is going on in this subject during several years. Many important models have been proposed in literature for improving the
A. Shabri, A. Rafidah, (UniKL MITEC)
core  

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

Beyond Prediction: Data, Baselines, Explanation, and Causation in Machine Learning for Food Insecurity

Food Safety and Health, EarlyView.
The gains from machine learning in nowcasting and forecasting food insecurity are still small and limited and cannot be observed in all countries. This review summarizes the public resources for data, corrects common misconceptions about model requirements, and establishes baseline requirements, explanations, causal inference, and equity in operational
Shabnam Mehboob, Azman Abdullah, Gunesh Kumar, Samreen Memon, Naila Afghan   +4 more
wiley   +1 more source

From Physiology to Bioheat Simulation: A Data‐Driven Framework for Core Temperature Initialization

Heat Transfer, EarlyView.
ABSTRACT Accurate initialization of core body temperature is a critical yet often overlooked component of bioheat transfer models, particularly when such models are applied to heterogeneous populations and real‐world environmental conditions. Conventional bioheat simulations typically rely on fixed or idealized core body temperature values derived from
David S. Rodríguez, Ana S. Acosta, Carol D. Vergara, Daniela Martínez, Sebastián Bermúdez, Cristian F. Rodríguez, Juan C. Cruz   +6 more
wiley   +1 more source

Modeling the Nexus Between Climate Risk, Energy Consumption, and Financial Market Performance in Emerging Countries

International Studies of Economics, EarlyView.
Abstract This paper examines the link between climate risk, energy consumption, and financial market performance in a sample of emerging countries over the period 2000–2024. The objective is to model the dynamic interactions between these three dimensions, in order to understand the extent to which energy dependence and exposure to climate risks ...
Abdelkader Mohamed Derbali
wiley   +1 more source

Small Area Consumption Estimates Combining Survey and Financial Footprints Data

Journal of Applied Econometrics, EarlyView.
ABSTRACT We estimate average equivalised consumption measures across 370 local authority districts in Great Britain, using small‐area estimation methods that combine information from a household budget survey, a much larger survey of local demographics and employment, and area‐level information on bank account outflows and energy consumption.
Peter Levell, Lars Nesheim, Gautam Vyas
wiley   +1 more source

Two Two‐Tier Stochastic Frontier Replications

Journal of Applied Econometrics, EarlyView.
ABSTRACT We replicate the two foundational studies which proposed the two‐tier stochastic frontier model, first in the cross‐sectional setting and then for the fixed effects panel data model. We explore matters of software then and now, different mathematical formulations of the likelihood, and alternative current software tools.
Alecos Papadopoulos, Christopher Parmeter   +1 more
wiley   +1 more source