Results 161 to 170 of about 156,378 (258)

Monte Carlo Method and GA-MLR-Based QSAR Modeling of NS5A Inhibitors against the Hepatitis C Virus. [PDF]

Molecules, 2022
Liman W, Oubahmane M, Hdoufane I, Bjij I, Villemin D, Daoud R, Cherqaoui D, El Allali A.   +7 more
europepmc   +1 more source

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

Advanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source

Simulation and Analysis of Imaging Process of Phosphor Screens for X-Ray Imaging of Streak Tube Using Geant4-Based Monte Carlo Method. [PDF]

Sensors (Basel)
Wang Z, Lin R, Liao Y, Tang L, Wu Z, Liu D, Zhong R, Zhang K.   +7 more
europepmc   +1 more source

Extension of the Aggregation-Volume-Bias Monte Carlo Method to the Calculation of Phase Properties of Solid Systems: A Lattice-Based Cluster Approach. [PDF]

J Phys Chem A, 2022
Chen B.
europepmc   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Reliability Indices Utlization in Combined Heat and Power ( CHP ) Optimal Operation

Majlesi Journal of Electrical Engineering
The reason that cogeneration is being used more compared to separate heat and power is because it is more efficient.  In this paper the goal is finding the optimized CHP system utility size and thermal storage considering reliability limits of boiler and
Hamed Hosseinnia, Dariush Nazarpour, Masoud Rezaei Benam   +2 more
doaj  

Comparison of Guide to Expression of Uncertainty in Measurement and Monte Carlo Method for Evaluating Gauge Factor Calibration Test Uncertainty of High-Temperature Wire Strain Gauge. [PDF]

Sensors (Basel)
Zhao Y, Zhang F, Ai Y, Tian J, Wang Z.
europepmc   +1 more source

Quantifying Distributions of Parameters for Cardiac Action Potential Models Using the Hamiltonian Monte Carlo Method. [PDF]

Comput Cardiol (2010), 2021
Nieto Ramos A, Herndon CJ, Fenton FH, Cherry EM.   +3 more
europepmc   +1 more source

Factorization Machine with Iterative Quantum Reverse Annealing: A Python Package for Batch Black‐Box Optimization With Reverse Quantum Annealing

Advanced Intelligent Discovery, EarlyView.
Factorization machine with iterative quantum reverse annealing (FMIRA) leverages quantum reverse annealing to perform batch black‐box optimization. Factorization machine with quantum annealing (FMQA) is a widely used python package for solving black‐box optimization problems using D‐Wave quantum annealers.
Andrejs Tučs, Ryo Tamura, Koji Tsuda
wiley   +1 more source

Design and Validation of a Monte Carlo Method for the Implementation of Noninvasive Wearable Devices for HbA1c Estimation Considering the Skin Effect. [PDF]

Micromachines (Basel)
Kwon TH, Hossain S, Turja MS, Kim KD.
europepmc   +1 more source