Hybrid physics-informed artificial intelligence for high-fidelity modeling and optimization of electrical systems. [PDF]
Nyangon J.
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Lightweight hybrid neural network with physics consistency regularization for lithium-ion battery state of health estimation. [PDF]
Zhang P +4 more
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A physics-informed neural network approach for estimating population-level pharmacokinetic parameters from aggregated concentration data. [PDF]
Tsiros P, Minadakis V, Sarimveis H.
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Forecasting secular variation using physics-informed neural networks for IGRF-14. [PDF]
Shakespeare-Rees N +6 more
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Parameter calibration method for car-following models under snowy weather conditions: Integrating an informer time series encoder and physics-informed neural networks. [PDF]
Sun Y, Li W, Yang M, Zhang X.
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Automating PINN-based kinematic resolution of robotic joints using robotic process automation frameworks. [PDF]
Agrawal P, Sekar P, Kushwaha KK.
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A temperature- and impedance-aware LSTM-PINN framework for physically consistent battery SOH prediction. [PDF]
Kumar PN +5 more
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Optimising pandemic response through vaccination strategies using neural networks. [PDF]
Zhai C, Chen P, Jin Z, Pitt D.
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A physics-informed machine learning framework for predicting and mitigating doxorubicin nanocarrier toxicity in normal cells. [PDF]
Rahdar A, Fathi-Karkan S.
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