Sentence examples for modeling and probabilistic from inspiring English sources
It deals with the use of computational fluid dynamics (CFD) fire modeling in conjunction with other important practical aspects in fire engineering such as artificial neural network (ANN), evacuation modeling, and probabilistic approach to assess the total fire safety system.
All data modeling and probabilistic sensitivity analyses were conducted using the software package TreeAge (TreeAge Software Inc., Williamstown, MA, USA).
In all of these models, clear separation is maintained between a) estimation in the range of observation (e.g., the derivation of a human POD using benchmark dose modeling and probabilistic cross-species, route, or duration adjustments) and b) extrapolation to low doses.
However, cost utility analysis using a suitable method of economic evaluation (such as decision modeling) and probabilistic sensitivity analysis may be useful approaches in the absence of data on variation of cancer-detection rate and response to treatment by absolute risk threshold.
In this work we use a stochastic modeling approach and probabilistic model checker to model and analyze the Na,K-pump which provides a new perspective on the study of the behavior of this system.
Probabilistic modeling is still a developing branch of computer science: operational research (for example probabilistic model-based prognosis) [1], decision making techniques and probabilistic modeling [2], artificial intelligence and machine learning.
Probabilistic Relational Models (PRMs Getoorr et al., 2002 ) and their extension ProBic (Van den Bulcke, 2009 ) are fully generative models that combine probabilistic modeling and relational logic.
The modeling approach, uncertainty analysis, and probabilistic optimization results are presented and discussed.
Most of them use vector-space and probabilistic modeling approaches, some of them are based on neural networks or graphs.
MLVA and probabilistic modeling provide a rigorous means to identify the most likely fine-scale environmental source.
The emphasis of her research is on Bayesian and probabilistic graphical modeling approaches for addressing challenges associated with modeling and prediction in real-world temporal systems.
