Sentence examples for probability modeling from inspiring English sources

NPMR is a flexible probability modeling system that can find the best subset of habitat factors influencing species occurrence.

Dispersion simulations are a particular important part of these studies as they both define the size of the clouds and give basis for detailed ignition probability modeling.

Due to variability in microstructural properties produced by differences in alloys and processing conditions, scientifically based probability modeling for life prediction and reliability is a challenging problem.

The essence of science based probability modeling of damage, evolution, and distribution is the formulation of a time dependent damage function that captures its functional dependence on all of the key internal and external variables, and their variability.

This chapter focuses on the need for science based probability modeling of damage evolution, and distribution for use in life cycle engineering and management (LCEM) of modem, high value-added engineered systems.

Working in the context of event detection for the MACHO LMC data, I will present an approach that combines much of the power of Bayesian probability modeling with the the efficiency and scalability typically associated with more ad-hoc machine learning approaches.

Applied Probability: Models and Intuition.

So, we have to have some kind of Probability Model.

Stuart Russell, ''Expressive probability models in science". In Proc.

Probability models on graphs date back to 1959.

ARIMA methods are based on the assumption that a probability model generates the time series data.