Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...
Abstract: Predictive maintenance is essential for ensuring the reliability and efficiency of wind energy systems. Traditional deep learning models for sensor fault detection rely solely on data-driven ...
Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...
This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...
ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...
Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis Lymphocytes play critical ...
1 State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China 2 State Key Laboratory of Mountain Bridge and Tunnel Engineering, ...
Google is testing a machine learning-powered tech in the U.S. to determine the age of users and filter content across all its products accordingly. The company said it will consider data from Google ...
The Kentucky Council on Postsecondary Education (CPE), in partnership with the Department for Community-Based Services (DCBS) and a consortium of postsecondary institutions, kicked off the Community ...
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