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Monte Carlo Method

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Comparison of ANN and XGBoost surrogate models trained on small numbers of building energy simulations.

PloS one
Surrogate optimisation holds a big promise for building energy optimisation studies due to its goal to replace the use of lengthy building energy simulations within an optimisation step with expendable local surrogate models that can quickly predict ...

Neural parameter calibration and uncertainty quantification for epidemic forecasting.

PloS one
The recent COVID-19 pandemic has thrown the importance of accurately forecasting contagion dynamics and learning infection parameters into sharp focus. At the same time, effective policy-making requires knowledge of the uncertainty on such prediction...

Weighted Expectile Regression Neural Networks for Right Censored Data.

Statistics in medicine
As a favorable alternative to the censored quantile regression, censored expectile regression has been popular in survival analysis due to its flexibility in modeling the heterogeneous effect of covariates. The existing weighted expectile regression ...

GraphBNC: Machine Learning-Aided Prediction of Interactions Between Metal Nanoclusters and Blood Proteins.

Advanced materials (Deerfield Beach, Fla.)
Hybrid nanostructures between biomolecules and inorganic nanomaterials constitute a largely unexplored field of research, with the potential for novel applications in bioimaging, biosensing, and nanomedicine. Developing such applications relies criti...

A Mode Evolution Metric to Extract Reaction Coordinates for Biomolecular Conformational Transitions.

Journal of chemical theory and computation
The complex, multidimensional energy landscape of biomolecules makes the extraction of suitable, nonintuitive collective variables (CVs) that describe their conformational transitions challenging. At present, dimensionality reduction approaches and m...

Dose prediction of CyberKnife Monte Carlo plan for lung cancer patients based on deep learning: robust learning of variable beam configurations.

Radiation oncology (London, England)
BACKGROUND: Accurate calculation of lung cancer dose using the Monte Carlo (MC) algorithm in CyberKnife (CK) is essential for precise planning. We aim to employ deep learning to directly predict the 3D dose distribution calculated by the MC algorithm...

The influence of neighbor selection on self-organized UAV swarm based on finite perception vision.

Bioinspiration & biomimetics
Recently, vision-based unmanned aerial vehicle (UAV) swarming has emerged as a promising alternative that can overcome the adaptability and scalability limitations of distributed and communication-based UAV swarm systems. While most vision-based cont...

Uncertainty Qualification for Deep Learning-Based Elementary Reaction Property Prediction.

Journal of chemical information and modeling
The prediction of the thermodynamic and kinetic properties of elementary reactions has shown rapid improvement due to the implementation of deep learning (DL) methods. While various studies have reported the success in predicting reaction properties,...

Grand canonical Monte Carlo and deep learning assisted enhanced sampling to characterize the distribution of Mg2+ and influence of the Drude polarizable force field on the stability of folded states of the twister ribozyme.

The Journal of chemical physics
Molecular dynamics simulations are crucial for understanding the structural and dynamical behavior of biomolecular systems, including the impact of their environment. However, there is a gap between the time scale of these simulations and that of rea...

Rheological modelling of apple puree based on machine learning combined Monte Carlo simulation: Insight into the fundamental light- particle structure interaction processes.

Food chemistry
In this work, apple purees from different particle concentration and verifying in size were reconstituted to investigate their impacts on rheological behaviors, optical properties and light interaction at 900-1650 nm. The optical scattering of differ...