Motivated metamodels
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Motivated metamodels synthesis of cause-effect reasoning and statistical metamodeling by Davis, Paul K.

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Published by RAND in Santa Monica, CA .
Written in English

Subjects:

  • Computer simulation,
  • Decision making

Book details:

Edition Notes

StatementPaul K. Davis, James H. Bigelow
SeriesMR (Rand Corporation) -- MR-1570
ContributionsBigelow, J. H, Rand Corporation
Classifications
LC ClassificationsQA76.9.C65 D395 2003
The Physical Object
Paginationxix, 65 p. :
Number of Pages65
ID Numbers
Open LibraryOL17067337M
ISBN 100833033190
LC Control Number2002155700

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"Motivated is full of practical suggestions for how to encourage students' participation in the mathematics classroom, but it is more than a how-to book. Instead, it's a 'why so' book it provides the reasons for why those instructional ideas work, thereby giving instructors the tools to think about their own teaching practices." /5(7).   This chapter is from the book This chapter is from the book Metadata Solutions: Using Metamodels, Repositories, XML, and Enterprise Portals to Generate Information on Demand Learn More Buy. Sample Metamodels. Metamodels can be purchased, downloaded, copied, or custom developed. Sometimes, metamodels are an inherent part of a metadata . Dean Allemang, Jim Hendler, in Semantic Web for the Working Ontologist (Second Edition), Metamodeling. Metamodeling is the name commonly given to the practice of using a model to describe another model as an instance. One feature of metamodeling is that it must be possible to assign properties to classes in the model. meta- and metamodels in a formal way Zinovy Diskin∗ Frame Inform Systems,Ltd. Riga, Latvia [email protected], [email protected] Abstract The paper suggests a formal framework to reason about metamodeling in a way independent of specifics of one or another metamodel and so encompassing such distinct metamodels as, say, relational, UML and : K. Baclawski, H. Kilov, A. Thalassinidis, K. Tyson, Zinovy Diskin.

MetaModels are data models you can configure in the Contao Backend. Every MetaModel consists of various attributes of certain data types. - MetaModels.   The increased computational power and software tools available to engineers have increased the use and dependence on modeling and computer simulation throughout the design process. These tools have given engineers the capability of designing highly complex systems and computer architectures that were previously unthinkable. Every complex design project, 4/5(3). Metamodels are functions with calibrated parameters, used as abstractions and simplifications of the simulation model. A metamodel exposes the system's input . To make the model fast and integrated, the model consists of theory-motivated metamodels describing the complete cause-effect chain, and is referred to as an Integrated Assessment Metamodel (IAMM) (Section 4). 4. Evaluation of the model: evaluation of IAMs has received more attention, but a common framework is by:

– Metamodeling, or meta-modeling, is the analysis, construction and development of the frames, rules, constraints, models and theories applicable and useful for modeling a predefined class of problems. Metamodels in the context of MDA are expressed using MOF. Motivated by the existing works, a novel metamodeling approach for building the ensemble metamodels is proposed in this paper. By thoroughly exploring the characteristics of regression-type and interpolation-type metamodels, some useful information is extracted from the feedback of the regression-type metamodels to further improve the Author: Cheng Yan, Jianfeng Zhu, Xiuli Shen, Jun Fan, Dong Mi, Zhengming Qian. Motivated Metamodels: Synthesis of Cause-Effect Reasoning and Statistical Metamodeling by Paul K. Davis An Introduction to Simulation Using GPSS/H by Thomas J. Schriber Data science and social research: epistemology, methods, technology and applications by N. Carlo Lauro. Metamodels are functions with calibrated parameters, used as abstractions and simplifications of the simulation model. A metamodel exposes the system's input-output relationship and can be used as an analysis tool for solving optimization problems or as a surrogate for building blocks in larger scale simulations.