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A Radial Basis Function (RBF -based suRBF -baseddelling approach usurrogategn of Experimodelling) technique wapproachto establish near-optimal initial process parameters arousinghich to focus the stuDesign
In this paper, we discuss the results of a Partitioning Interwell Tracer Test (PITT) performed in a large scale experiment with a well-defined TCE spill, and present a novel combined analytical numerical inverse modelling approach using measured concentration profiles within a TCE plume to predict the distribution of the DNAPL in a virtual vertical plane of the source.
The risk is calculated using a standard logistic regression modelling approach using the casemix variables.
In sensitivity analyses, we also used an alternate stepwise modelling approach, using the significance level of p<0.05, to justify the inclusion of covariates into the regression models.
This paper investigates the impacts of increase or decrease in plantations and climate variability on streamflow using two approaches: the sensitivity-based approach (including a non-parametric model and six Budyko framework based models) and the hydrological modelling approach (using Xinanjiang and SIMHYD models) for three medium sized catchments in Australia.
This paper aims to present a new systemic modelling approach using the unified modelling language (UML) and Multi-Agents Systems (MAS) to model the complexity and analyze the risks of maintenance activities within a Liquefied Petroleum Gas (LPG) supply chain.
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The reduced order modelling approach uses prediction data for the thermo-mechanical behaviour.
TGS modelling approach uses a simple algorithm resulting from the best accumulated combination of candidate gene polymorphisms.
Chiu et al. [29] proposed a pixel-wise color background modeling approach using probability theory and clustering.
We present results of our activity modeling approach using videos of both high-resolution single individual activities and ground plane surveillance activities.
The models were built following a statistical approach using a continuous Hidden Markov Model, a black-box state space modeling approach using Recursive Multi-Layer Perceptrons, and a histrogram-based approach.
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