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“Can Modelling Be Taught and Learnt?” – A Commentary
(2011-01-01)
The questions, whether mathematical modelling can be learnt and what we know from empirical research, are highly relevant not only for the current research on modelling, but they are as well essential for curricular changes ...
A predictive view of Bayesian clustering
(ELSEVIER, 2006)
This work considers probability models for partitions of a set of n elements using a predictive approach, i.e., models that are specified in terms of the conditional probability of either joining an already existing cluster ...
A systemic approach to analyze integrated energy system modeling tools: A review of national models
We reviewed the literature focusing on nineteen integrated Energy System Models (ESMs) to: (i) identify the
capabilities and shortcomings of current ESMs to analyze adequately the transition towards a low-carbon energy
system; ...
Systematic review and comparison of modeling ETL processes in data warehouse
(08/23/2010)
Abstract:
In a Data Warehouse (DW), ETL processes (Extraction, Transformation, Load) are responsible for extracting, transforming and loading data from the data sources into the DW. A good design of these processes in the ...
MOOGLE: a metamodel-based model search engine
(SPRINGER HEIDELBERGHEIDELBERG, 2012)
Models are becoming increasingly important in the software development process. As a consequence, the number of models being used is increasing, and so is the need for efficient mechanisms to search them. Various existing ...
Business model dynamics: a case survey
(Universidad de Talca, 2009)
Comparison of friction models applied to a control valve
(PERGAMON-ELSEVIER SCIENCE LTD, 2008)
Eight different models to represent the effect of friction in control valves are presented: four models based on physical principles and four empirical ones. The physical models, both static and dynamic, have the same ...
Tree-structured smooth transition models
(Escola de Pós-Graduação em Economia da FGV, 2005-11-03)
The goal of this paper is to introduce a class of tree-structured models that combines aspects of regression trees and smooth transition regression models. The model is called the Smooth Transition Regression Tree (STR-Tree). ...