Results 191 to 200 of about 857,070 (293)

Plate Waste Forecasting Using the Monte Carlo Method for Effective Decision Making in Latvian Schools. [PDF]

Nutrients, 2022
Kodors S, Zvaigzne A, Litavniece L, Lonska J, Silicka I, Kotane I, Deksne J.   +6 more
europepmc   +1 more source

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

Advanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan, Ankeer Abuduhebaier, Haojin Zhou, Jiaqi Wang   +3 more
wiley   +1 more source

Thermal Energy Transfer between Helium Gas and Graphene Surface According to Molecular Dynamics Simulations and the Monte Carlo Method. [PDF]

Nanomaterials (Basel), 2022
Zhang L, Ban H.
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

Corrigendum to "Seemingly unrelated time series model for forecasting the peak and short-term electricity demand: Evidence from the Kalman filtered Monte Carlo method" [Heliyon Volume 9, Issue 8, August 2023, Article e18821]. [PDF]

Heliyon
Owusu FK, Amoako-Yirenkyi P, Frempong NK, Omari-Sasu AY, Mensah IA, Martin H, Sakyi A.   +6 more
europepmc   +1 more source

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

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  

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