Results 211 to 220 of about 117,319,651 (289)

A Comprehensive Comparative Study of Active Learning Schemes for Nanophotonics Design

Advanced Intelligent Discovery, EarlyView.
Active learning (AL) strategies are benchmarked for the binary design of planar multilayer nanophotonic structures. Factorization machines combined with quantum annealing (QA) become effective as dimensionality increases. Hybrid QA provides the strongest results for 100‐layer problems, highlighting the importance of optimization method selection in ...
Serang Jung, Seongmin Kim, Jaehyun Park, Chaeyoung Park, Zhihao Xu, Sanghyo Hwang, Baiqing Ye, Youn sang Kim, Sun‐Kyung Kim, Tengfei Luo, Eungkyu Lee   +10 more
wiley   +1 more source

Prediction model for early neurological deterioration in large artery atherosclerotic stroke. [PDF]

Front Neurol
Feng L, Zhang C, Zhou J, Zhang X, Guo J, Zhang B.   +5 more
europepmc   +1 more source

Interpretable Short‐Term Electric Load Forecasting

Advanced Intelligent Systems, EarlyView.
A temporal fusion transformer is implemented to generate day‐ahead forecasts of the hourly electrical load of a departmentbuilding at an Italian university. A forecasting performance improvement of more than 25% compared with established benchmark models and a provision of inherent robust interpretability insights reveal the potential of this model for
Alessandro Nicola, Giorgia Ghione, Vincenzo Randazzo, Vincenzo Franzitta, Marco Badami, Eros Pasero, Giansalvo Cirrincione   +6 more
wiley   +1 more source

Multivariate control based on recurrent wavelet neural network for wastewater treatment process. [PDF]

PLoS One
Fang Y, Su Y, Li Y.
europepmc   +1 more source

Distributed State Estimation for Mobile Robots in LiDAR Sensor Networks With Intermittent Inertial Measurements

Advanced Intelligent Systems, EarlyView.
A scalable distributed observer framework for LiDAR sensor networks is presented for robust tracking and pose estimation of mobile robots. By combining adaptable 3D detection, clustering‐based communication reduction, and intermittent inertial fusion, accurate and efficient estimation is achieved under occlusions and sensing constraints, with formally ...
Isabella Luppi, Ehsan Hashemi
wiley   +1 more source

Comment on: Identification in the linear errors in variables model [PDF]

Bekker, P.A.
core  

Very short-term production prediction for photovoltaic plants using Temporal Convolutional Networks. [PDF]

PLoS One
Samaras L, García-Barriocanal E, Sicilia MA, García LG.   +3 more
europepmc   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source

A machine learning-based framework for predicting type 2 diabetes mellitus using hematological indices. [PDF]

Am Heart J Plus
Kamkar N, Behzadi S, Mahdavizadeh V, Maali Tafti M, Mansoori A, Poudineh M, Esmaily H, Ghayour-Mobarhan M.   +7 more
europepmc   +1 more source

Integration of Liquid Handling Robotics, Turbidimetry, and Machine Learning Toward Inverse Design of Lower Critical Solution Temperature Polymer Formulations

Advanced Intelligent Systems, EarlyView.
An integrated OT‐2/plate reader platform automates LCST cloud point measurement of NIPAM‐co‐DMAEMA copolymers across high‐dimensional formulation spaces. Machine learning trained on the resulting high‐throughput datasets achieves R2 up to 0.96 and enables inverse design of polymer formulations to target transition temperatures with <1% error.
Lachlan Alexander, Vianna F. Jafari, Tanja Junkers   +2 more
wiley   +1 more source