Results 51 to 60 of about 3,204 (210)
Machine learning driven many‐objective moving horizon scheduling optimization
Abstract Industrial electrification can decarbonize chemical manufacturing, but it exposes operations to volatile electricity prices and carbon intensities. This work develops a machine learning‐enhanced many‐objective moving horizon scheduling framework that predicts objective correlation groupings from 48‐hour price and emission‐intensity profiles ...
Hongxuan Wang, Andrew Allman
wiley +1 more source
Hybrid Decision-making Method for Emergency Response System of Unattended Train Operation Metro
Suitable selection of the emergency alternatives is a critical issue in emergency response system of Unattended Train Operation (UTO) metro system of China.
Bobo Zhao, Tao Tang, Bin Ning, Wei Zheng
doaj +1 more source
The design and evaluation of algorithms for adaptive stochastic control of the reservoir function of a water reservoir using an artificial intelligence method (learned fuzzy model) are described in this article.
Kozel Tomas, Stary Milos
doaj +1 more source
Abstract The rapid growth of AI data centers (AIDCs) is intensifying stress on power systems and exposing operators to volatile electricity markets. This work develops a process‐informed co‐optimization framework that integrates liquid air energy storage (LAES) with AIDC operation. Unlike black‐box storage models, the proposed formulation captures LAES
Zhicong Fang +3 more
wiley +1 more source
Introduction: Improved survival from out-of-hospital cardiac arrest with good neurological outcome was observed in association with dispatcher-assisted cardiopulmonary resuscitation, increasing the number of bystander-initiated resuscitations and ...
Guglielmo Imbriaco, Nicola Ramacciati
doaj +1 more source
Data‐Driven High‐Throughput Volume Fraction Estimation From X‐Ray Diffraction Patterns
Long exposure times and the need for manual evaluation limit the use of X‐ray diffraction in high‐throughput applications. This study presents a data‐driven approach addressing both issues. HiVE (a method for High‐throughput Volume fraction Estimation) performs composition estimation for high‐noise XRD patterns produced using polychromatic emission ...
Hawo H. Höfer +6 more
wiley +1 more source
An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto +5 more
wiley +1 more source
Abstract Research Summary Using detailed plant‐ and individual‐level data from a major Japanese cotton spinning company in the early 20th century, we examine the within‐firm allocation of skilled human capital in conjunction with investment in physical capital, accompanying the firm's evolving strategic priorities.
Shotaro Yamaguchi +3 more
wiley +1 more source
ABSTRACT Background The impact of presumptive coverage policies for work‐related mental health disorders has not been extensively studied to date. Using data from the Association of Workers’ Compensation Boards of Canada (AWCBC), our objectives were to describe the evolution of compensated mental health conditions, and to explore the association ...
Quentin Durand‐Moreau +3 more
wiley +1 more source
Background Out‐of‐hospital cardiac arrests (OHCAs) are an important global health burden, and risk factors for patients with dispatcher‐unrecognized OHCAs have not yet been well investigated.
Min Seol Seo +8 more
doaj +1 more source

