Multimodal Learning with Rashomon Analysis for Battery Discharge Capacity Prediction
Advanced Intelligent Discovery, EarlyView.Multimodal fusion integrates composition, crystal‐structure, and radial‐distribution descriptors to predict battery discharge capacity. Rashomon analysis across near‐optimal models reveals that explanatory variation is structured rather than arbitrary, separating stable mechanistic signals from model‐contingent attributions and providing a more ...
Jue Gong +4 more
wiley +1 more source
A global dataset of immigration flow composition by age, sex and educational attainment. [PDF]
Sci DataYildiz D, Abel GJ.
europepmc +1 more source
Bootstrap Approximation to Prediction MSE for State-Space Models with Estimated Parameters
, 2004 We propose a simple but general bootstrap method for estimating the Prediction Mean Square Error (PMSE) of the state vector predictors when the unknown model parameters are estimated from the observed series.
Pfeffermann, Danny, Tiller, Richard
core
Data‐Efficient Cycle‐Level Capacity Prediction Using 1D Deep Convolutional Network
Advanced Intelligent Discovery, EarlyView.We introduce DeepBat, a deep learning framework featuring a 1D convolutional backbone designed to extract latent degradation patterns from a microstructurally diverse electrode dataset. By learning complex formulation–performance relationships, the model accurately predicts long‐term specific discharge capacity using limited early‐cycle data, providing
Tao Huang +16 more
wiley +1 more source
Delineating season-specific hotspots: A spatio-temporal risk assessment of neck blast disease in rainfed and irrigated ecosystems of Cumilla District, Bangladesh. [PDF]
PLoS OneRashid MM +10 more
europepmc +1 more source
A Hybrid Transfer Learning Framework for Brain Tumor Diagnosis
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.A novel hybrid transfer learning approach for brain tumor classification achieves 99.47% accuracy using magnetic resonance imaging (MRI) images. By combining image preprocessing, ensemble deep learning, and explainable artificial intelligence (XAI) techniques like gradient‐weighted class activation mapping and SHapley Additive exPlanations (SHAP), the ...
Sadia Islam Tonni +11 more
wiley +1 more source
Applications of Machine Learning in Noninvasive Anemia Diagnosis: A Systematic Review Based on Cross-Industry Standard Process for Data Mining. [PDF]
Health Sci RepGhahroudi MH +2 more
europepmc +1 more source
Predicting Performance of Hall Effect Ion Source Using Machine Learning
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +1 more source
Evaluating molecular docking for binding affinity predictions: a systematic analysis of key parameters and the utility of AlphaFold2 structures for the Schrödinger dataset. [PDF]
J Comput Aided Mol DesTornesakis K +3 more
europepmc +1 more source
Collaborative Visual Localization for Modular Self‐Reconfigurable Robots
Advanced Intelligent Systems, EarlyView.Relative localization in modular self‐reconfigurable robots is challenged by hardware limitations, constrained fields of view, and sensor faults. This paper, based on the SnailBot platform, presents a vision‐based collaborative localization method that combines ArUco markers with learning‐based algorithms to enable robust pose estimation from ...
Guanqi Liang +4 more
wiley +1 more source