Results 101 to 110 of about 38,464 (255)

Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization

Advanced Electronic Materials, EarlyView.
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali, David Lehninger, Florencio Sánchez, Ignasi Fina   +3 more
wiley   +1 more source

UWB Indoor Localization Based on XGBoost NLOS Identification and DS-TWR Ranging [PDF]

Radioengineering
Indoor environments present significant challenges for ultra-wideband (UWB) localization due to ranging errors and non-line-of-sight (NLOS) propagation.
X. Yao Z. Xu, G. Liu
doaj  

Machine learning–driven design of catalytic processes for sulfur dioxide oxidation: Lessons from the trenches

AIChE Journal, EarlyView.
Abstract Despite the growing use of ML in chemical engineering, the catalytic conversion of sulfur dioxide (SO2) to sulfur trioxide (SO3) remains underexplored from a data‐driven modeling perspective. This study evaluates an integrated workflow for literature‐derived SO2 oxidation data, combining data curation, preprocessing assessment, machine ...
Farough Agin, Jules Thibault, Clémence Fauteux‐Lefebvre   +2 more
wiley   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Enhancing spatial prediction of groundwater-prone areas through optimization of a boosting algorithm with bio-inspired metaheuristic algorithms

Applied Water Science
Groundwater resources are essential for ensuring a consistent water supply in many regions. Groundwater potential maps (GPMs) can be utilized in many ways to estimate the quantity, quality, and distribution of subsurface water, supporting the decision ...
Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Sani I. Abba, Farman Ali, Soo-Mi Choi   +4 more
doaj   +1 more source

Research on intelligent fault identification method of coalfield based on the PSO-XGBoost algorithm

矿业科学学报
In order to further improve the accuracy and efficiency of underground fault identification, an intelligent fault recognition model based on the extreme gradient boosting tree (XGBoost) machine learning algorithm was constructed for coal seam faults ...
LIN Peng, SUN Cheng, REN Ke, LIU Yulin, LI Yang   +4 more
doaj   +1 more source

A Multimodal Intelligent System for Human Digital Twin Simulation with Continuous Kinematic Data Tracking, Biometric Prognosis, and Cognitive State Feedback in Industrial Environments

Advanced Intelligent Discovery, EarlyView.
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury, Sebastian Gratz‐Kelly, Eric Wagner, Paul Motzki, Martina Lehser   +4 more
wiley   +1 more source

Real-Time Jaundice Detection in Neonates Based on Machine Learning Models

BioMedInformatics
Introduction: Despite the many attempts made by researchers to diagnose jaundice non-invasively using machine learning techniques, the low amount of data used to build their models remains the key factor limiting the performance of their models ...
Ahmad Yaseen Abdulrazzak, Saleem Latif Mohammed, Ali Al-Naji, Javaan Chahl   +3 more
doaj   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Multiple Disease Prediction Using Machine Learning Algorithm (XGBoost Algorithm)

International Journal of Information Technology and Computer Engineering
Every day, many individuals encounter different illnesses. The prognosis of a disease is the most pivotal part of treatment. The enormous increase in healthcare and medical data has enabled accurate medical data analysis, which aids in early sickness discovery and proactive patient care.
null Shaik Sihab, null Syed Akber Quadri, null Mohammed Abdul Ibrahim, null Mrs.T Anita   +3 more
openaire   +1 more source