Results 91 to 100 of about 21,185 (243)

Comparative Study of the ARIMA Method and Multiple Linear Regression in Metro City Population Growth Projections

open access: yesJournal of Applied Informatics and Computing
This study aims to compare the effectiveness of the ARIMA (Autoregressive Integrated Moving Average) method and multiple linear regression in projecting population growth in Metro City, Lampung.
Tri Aristi Saputri   +2 more
doaj   +1 more source

Analysis of Models to Estimate Morbidity Rates of Respiratory Diseases Through Deep Learning

open access: yesTropical Medicine &International Health, EarlyView.
ABSTRACT Respiratory diseases remain a challenge in Brazil due to socioeconomic inequalities and environmental risks that intensify population vulnerability. This study compared XGBoost with a deep learning model using stacked Gated Recurrent Units (GRU), trained with morbidity data from respiratory diseases and exogenous variables such as per capita ...
Liliane Moreira Nery   +6 more
wiley   +1 more source

Forecasting Wheat Production in Libya Using ARIMA Model-ARIMA

open access: yesمجلة آفاق للدراسات الإنسانية والتطبيقية
The wheat crop is a strategic crop in Libya as a food crop and a raw material for some food industries. The study aimed to predict the amount of wheat production in context of Libya during the next six years from 2023-2028. The Auto-regressive Integrated Moving Average (ARIMA) model has been used and relied on Food and Agriculture Organization data ...
openaire   +1 more source

Unveiling Stock Market Trends by Deep Learning Insights With Correction Factor and Recurrent Neural Networks

open access: yesExpert Systems, Volume 43, Issue 5, May 2026.
ABSTRACT Understanding financial behaviour, particularly in the stock market, has attracted significant interest in recent years due to advancements in artificial intelligence and its impact on the global economy. The field of stock market prediction, which explores the interaction between finance and computer science to create predictive models, aims ...
Jair O. González   +4 more
wiley   +1 more source

A Sequence‐to‐Sequence Approach for Short‐Term Temperature Prediction With Data Decomposition and Reconstruction

open access: yesNatural Resource Modeling, Volume 39, Issue 2, May 2026.
ABSTRACT Temperature is an important factor affecting daily life, and accurate multi‐step temperature prediction can provide essential support for weather prediction, energy management, agricultural planning, and disaster mitigation. However, as the prediction horizon extends, the nonlinear nature of temperature data becomes more prominent, making it ...
Baohe Liu   +4 more
wiley   +1 more source

Dilation Device Use and Concomitant Antegrade Stenting are Associated With Procedure‐related Early Adverse Events After Endoscopic Ultrasound‐guided Hepaticogastrostomy: A Retrospective Multicenter Study

open access: yesDEN Open, Volume 6, Issue 1, April 2026.
This multicenter study identified use of dilation devices and antegrade stenting are risk factors for procedure‐related early adverse events following endoscopic ultrasound‐guided hepaticogastrostomy. ABSTRACT Objectives Endoscopic ultrasound‐guided hepaticogastrostomy (EUS‐HGS) is useful in cases of endoscopic retrograde cholangiopancreatography ...
Shinichi Hashimoto   +19 more
wiley   +1 more source

Combined Effects of Fat‐Tail and Spread Forecasting on Pairs Trading: A Hybrid Model Based on Integrating VAR With GRU Models

open access: yesJournal of Forecasting, Volume 45, Issue 3, Page 1110-1128, April 2026.
ABSTRACT Pairs trading, a popular algorithmic trading strategy, exploits the short‐term price difference (spread) between two comoving assets. Empirically, the spread distribution of most assets in pairs trading has a fat‐tail characteristic that does not follow a normal distribution.
Yuhee Kwon, Youngsoo Choi
wiley   +1 more source

Prognostics and Health Management in Polymer Electrolyte Fuel Cells: Current Trends, Challenges, and Future Directions

open access: yesFuel Cells, Volume 26, Issue 2, April 2026.
ABSTRACT Prognostics and health management are crucial for the reliability and lifetime assessment of polymer electrolyte fuel cells (PEFCs). Here, we review the current advances on this topic, focusing mainly on key degradation mechanisms and methodologies such as physics‐aware, data‐driven, and hybrid modeling approaches.
Farideh Abdollahi   +5 more
wiley   +1 more source

Long-Term Projections of Patients Undertaking Renal Replacement Therapy Under the Universal Coverage Scheme in Thailand

open access: yesRisk Management and Healthcare Policy, 2020
Noppakun Thammatacharee, 1, 2 Rapeepong Suphanchaimat 2, 3 1Health Systems Research Institute, Nonthaburi, Thailand; 2International Health Policy Program (IHPP), the Ministry of Public Health, Nonthaburi, Thailand; 3Division of Epidemiology ...
Thammatacharee N, Suphanchaimat R
doaj  

Deep Quake Dynamics: A Multimodal Fault‐Aware Approach to Earthquake Magnitude and Occurrence Time Forecasting

open access: yesGeoscience Data Journal, Volume 13, Issue 2, April 2026.
EQMT integrates earthquake catalog data, fault‐network geometry, engineered features, and graph embeddings in a unified framework for forecasting earthquake magnitude and occurrence time. The framework is designed to reflect inter‐fault spatial dependencies together with temporal seismic patterns, addressing limitations of approaches based only on ...
Kiymet Kaya   +5 more
wiley   +1 more source

Home - About - Disclaimer - Privacy