Results 51 to 60 of about 9,313 (254)

Spatiotemporally Combined Dimensionality Reduction Algorithm for Optimizing Long-term Operation of Multi-reservoir Systems

Renmin Zhujiang, 2023
To alleviate the “curse of dimensionality” and improve the solution efficiency while ensuring the quality of solutions in optimizing the operation of multi-reservoir systems,this paper proposes a spatiotemporally combined dimensionality reduction ...
CHEN Jia, ZHANG Hanjun, XU Nan
doaj  

Using machine learning to identify top predictors for nurses’ willingness to report medication errors

Array, 2020
This paper presents a novel methodology to analyze nurses’ willingness to report medication errors. Parallel Extreme Learning Machines were applied to identify the top interpersonal and organizational predictors and Self-Organizing Maps to create ...
Renjie Hu, Amany Farag, Kaj-Mikael Björk, Amaury Lendasse   +3 more
doaj   +1 more source

AI‐Physics‐Experiment Trinity for Integrated Protein Dynamics Modeling

Advanced Science, EarlyView.
This review unites experiments, physics‐based simulations, and AI as a synergistic triad for protein dynamics modeling. It highlights integrative strategies, resolves sampling and forcefield bottlenecks, and outlines challenges and future directions for accurate, interpretable conformational ensemble prediction.
Chen Shi, Minying Low, Peng Xiu, Kresten Lindorff‐Larsen, Yong Wang   +4 more
wiley   +1 more source

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

Advanced Intelligent Discovery, EarlyView.
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

A Survey on Hybrid Feature Selection Methods in Microarray Gene Expression Data for Cancer Classification

IEEE Access, 2019
The emergence of DNA Microarray technology has enabled researchers to analyze the expression level of thousands of genes simultaneously. The Microarray data analysis is the process of finding the most informative genes as well as remove redundant and ...
Nada Almugren, Hala Alshamlan
doaj   +1 more source

Interpretable Machine Learning for Bandgap Prediction and Descriptor‐Guided Design Rules of Phosphates

Advanced Intelligent Discovery, EarlyView.
An explainable CatBoost model was trained to predict the bandgaps of 474 phosphate crystals based on composition and density descriptors. SHAP analysis identified two key variables—d‐electron‐count dispersion and atomic‐density dispersion—as the primary drivers of the model's predictions.
Wenhu Wang, Abudukadi Tudi, Ran An, Zhihua Yang   +3 more
wiley   +1 more source

High-Dimensional Numerical Methods for Nonlocal Models

Mathematics
Nonlocal models offer a unified framework for describing long-range spatial interactions and temporal memory effects. The review briefly outlines several representative physical problems, including anomalous diffusion, material fracture, viscoelastic ...
Yujing Jia, Dongbo Wang, Xu Guo
doaj   +1 more source

Robust Reinforcement Learning Control Framework for a Quadrotor Unmanned Aerial Vehicle Using Critic Neural Network

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Quadrotor unmanned aerial vehicle control is critical to maintain flight safety and efficiency, especially when facing external disturbances and model uncertainties. This article presents a robust reinforcement learning control scheme to deal with these challenges.
Yu Cai, Yefeng Yang, Tao Huang, Boyang Li   +3 more
wiley   +1 more source

Altered by Gold: A Comparative Zooarchaeological Analysis of 19th to 20th Century Chinese and British Migrants in Ravenswood, a Northern Queensland Gold Mining Town

Archaeology in Oceania, EarlyView.
ABSTRACT Gold discoveries transformed the 19th century British colony of Queensland, Australia, driving migration, a second wave of pastoral expansion northwards, and an increasingly diverse population. This study presents a comparative and contextual zooarchaeological analysis of British and southern Chinese food waste—globally significant migrant ...
Marc Cheeseman
wiley   +1 more source