Results 31 to 40 of about 636 (160)

A mixed-method to numerical simulation of variable order stochastic advection diffusion equations

Alexandria Engineering Journal
The study of stochastic problems is very important and there is an increasing demand for investigating the behavior of a number of sophisticated dynamical systems in different areas of science as well as in engineering and finance.
H. Jafari, R.M. Ganji, S. Salati, S.J. Johnston   +3 more
doaj   +1 more source

Radiation Transport in Random Media With Large Fluctuations

EPJ Web of Conferences, 2017
Neutral particle transport in media exhibiting large and complex material property spatial variation is modeled by representing cross sections as lognormal random functions of space and generated through a nonlinear memory-less transformation of a ...
Olson Aaron, Prinja Anil, Franke Brian
doaj   +1 more source

Parametric Transient Stability Constrained Optimal Power Flow Solved by Polynomial Approximation Based on the Stochastic Collocation Method

Energies, 2022
To better respond to the impact of power system-uncertain parameters on transient stability, a novel model named the parametric transient stability constrained optimal power flow (parametric TSCOPF) is proposed.
Bingqing Xia, Hao Wu, Wenbin Yang, Lu Cao, Yonghua Song   +4 more
doaj   +1 more source

Pulse‐Engineered Synaptic Linearity and Non‐Volatile Memory in MoO3/TiO2 Bilayer Memristors for Neuromorphic Image Recognition

Advanced Electronic Materials, EarlyView.
Pulse‐protocol optimization in an Au/MoO3/TiO2/FTO bilayer memristor enables linear analog synaptic conductance modulation along with digital resistive switching for memory. Controlled filament evolution produces stable learning‐forgetting characteristics with low nonlinearity, resulting in significantly enhanced neural network inference accuracy for ...
Girish Chandrashekar, Atul Thakre, R. Thamankar   +2 more
wiley   +1 more source

Efficient Solutions for Stochastic Fractional Differential Equations with a Neutral Delay Using Jacobi Poly-Fractonomials

Mathematics
This paper introduces a novel numerical technique for solving fractional stochastic differential equations with neutral delays. The method employs a stepwise collocation scheme with Jacobi poly-fractonomials to consider unknown stochastic processes.
Afshin Babaei, Sedigheh Banihashemi, Behrouz Parsa Moghaddam, Arman Dabiri, Alexandra Galhano   +4 more
doaj   +1 more source

Residual Strength Prediction of Chemically Reactive Two‐Phase Nanofluid Flow in a Bingham–Papanastasiou Rheological Theory Using a Morlet‐Based Wavelet Neural Network Approach

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT The behavior of nanofluid flow involving a zero‐mass flux condition has received considerable interest because of a realistic scenario. In reality, this condition confines the optimistic accumulation or disappearance of nanoparticles past a sheet, constructing a more physically realistic demonstration through several applications, such as heat
Umair Khan, Hamza Rauf, Aurang Zaib, J. K. Madhukesh   +3 more
wiley   +1 more source

Automated Data‐Efficient Symbolic Regression for Interpretable Bioprocess Model Development

Biotechnology and Bioengineering, EarlyView.
ABSTRACT Bioprocessing is central to the sustainable manufacture of pharmaceuticals, food products, and renewable chemicals. Consequently, developing high‐fidelity kinetic models to facilitate accurate process prediction, optimisation, and scale‐up is a top research priority.
Luca Riezzo, Alexander Rogers, Harry Kay, Dongda Zhang   +3 more
wiley   +1 more source

Learning Rocking Dynamics From Sparse Shake‐Table Data With Interpretable Physics‐Informed Neural Networks

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT We present a hybrid interpretable Physics‐Informed Neural Network Long‐Short Term Memory (Hybrid PINN LSTM) framework for predicting the seismic response of rocking blocks. Existing analytical models rely on uncertain idealizations, while purely data‐driven and machine‐learning approaches lack physical consistency and interpretability.
Shirley Shen, Christian Málaga‐Chuquitaype   +1 more
wiley   +1 more source

A Hybrid Fractional Chebyshev–Legendre Spectral Collocation Method for Hamilton–Jacobi–Bellman Equations

IEEE Access
Stochastic optimal control problems are commonly formulated as optimization problems constrained by stochastic dynamical systems, whose value functions satisfy Hamilton–Jacobi–Bellman (HJB) equations.
Alvian Alif Hidayatullah, Subchan Subchan, Sena Safarina, Tahiyatul Asfihani, R. Mohamad Atok, Irma Fitria, Andriyansah, Kasno Pamungkas   +7 more
doaj   +1 more source

Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models

Journal of Forecasting, EarlyView.
ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly, Pooja Sengupta, Divya Aggarwal   +2 more
wiley   +1 more source