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DETERMINATION OF THE MOST RELIABLE GLASS PROPERTY VALUES BY THE SCIGLASS INFORMATION SYSTEM

Mazurin Oleg, Gankin Yuriy

Open publisher page 3 citations

Abstract

The latest versions of commercially available glass property databases are powerful tools of predicting glass properties. It is possible to predict properties by using two kinds of models: statistical and structural ones. Most of the known statistical models for prediction of glass properties are polynomials obtained by approximation of a set of data points belonging to a selected composition area. Structural models are algorithms permitting calculation of glass properties from their compositions on the basis of the knowledge or suppositions on a glass structure and chemical interaction between components. A scientist can produce his/her own statistical model for prediction of properties of a given glass composition on the base of selected literature data. As to structural models, a selection of data taken from a database should be used to choose the most reliable model among the existing ones and determine a model error.

About this research paper

What this paper is about

The latest versions of commercially available glass property databases are powerful tools of predicting glass properties. It is possible to predict properties by using two kinds of models: statistical and structural ones. Most of the known statistical models for prediction of glass properties are polynomials obtained by approximation of a set of data points belonging to a selected composition area. Structural models are algorithms permitting calculation of glass properties from their compositions on the basis of the knowledge or suppositions on a glass structure and chemical interaction between components. A scientist can produce his/her own statistical model for prediction of properties of a given glass composition on the base of selected literature data. As to structural models, a selection of data taken from a database should be used to choose the most reliable model among the existing ones and determine a model error.

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Available abstract

The latest versions of commercially available glass property databases are powerful tools of predicting glass properties. It is possible to predict properties by using two kinds of models: statistical and structural ones. Most of the known statistical models for prediction of glass properties are polynomials obtained by approximation of a set of data points belonging to a selected composition area. Structural models are algorithms permitting calculation of glass properties from their compositions on the basis of the knowledge or suppositions on a glass structure and chemical interaction between components. A scientist can produce his/her own statistical model for prediction of properties of a given glass composition on the base of selected literature data. As to structural models, a selection of data taken from a database should be used to choose the most reliable model among the existing ones and determine a model error.

Key concepts: Property (philosophy), Set (abstract data type), Statistical model, Basis (linear algebra), Base (topology), Computer science, Statistical analysis, Data set

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DETERMINATION OF THE MOST RELIABLE GLASS PROPERTY VALUES BY THE SCIGLASS INFORMATION SYSTEM — Research Paper | ScholarLens