Advanced Energy Materials, EarlyView.In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu +6 more
wiley +1 more source
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
Advanced Energy Materials, EarlyView.In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source
Early Prediction of Dementia Using Feature Extraction Battery (FEB) and Optimized Support Vector Machine (SVM) for Classification. [PDF]
Biomedicines, 2023 Javeed A +6 more
europepmc +1 more source
Bidding Strategy with Forecast Technology Based on Support Vector Machine in Electrcity Market
, 2007 The participants of the electricity market concern very much the market price evolution. Various technologies have been developed for price forecast. SVM (Support Vector Machine) has shown its good performance in market price forecast. Two approaches for
Catalão +9 more
core +1 more source
The Role of Artificial Intelligence in Medication Management for Older Adults: A Systematic Review
AGING MEDICINE, EarlyView.Artificial intelligence enhances medication management for older adults by improving adherence, personalizing treatment, and predicting risks. Despite benefits, challenges remain in usability, trust, ethics, and system integration. Successful adoption requires user‐centered design, ethical safeguards, and seamless healthcare integration to ensure safe,
Dipak Chandra Das +9 more
wiley +1 more source
An improved accurate classification method for online education resources based on support vector machine (SVM): Algorithm and experiment. [PDF]
Educ Inf Technol (Dordr), 2022 Quan Z, Pu L.
europepmc +1 more source
Advanced Intelligent Discovery, EarlyView.In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley +1 more source
Classification of Low Earth Orbit (LEO) Resident Space Objects' (RSO) Light Curves Using a Support Vector Machine (SVM) and Long Short-Term Memory (LSTM). [PDF]
Sensors (Basel), 2023 Qashoa R, Lee R.
europepmc +1 more source
AAGLMES: an intelligent expert system realization of adaptive autonomy using generalized linear models [PDF]
, 2010 —We earlier introduced a novel framework for realization of Adaptive Autonomy (AA) in human-automation interaction (HAI). This study presents an expert system for realization of AA, using Support Vector Machine (SVM), referred to as Adaptive Autonomy
Fereidunian, Alireza. +3 more
core
Advanced Intelligent Discovery, EarlyView.This study applies QSAR‐based new approach methodologies to 90 synthetic tattoo and permanent makeup pigments, revealing systemic links between their physicochemical properties and absorption, distribution, metabolism, and elimination profiles. The correlation‐driven analysis using SwissADME, ChemBCPP, and principal component analysis uncovers insights
Girija Bansod +10 more
wiley +1 more source