E3S Web Conf.
Volume 49, 2018SOLINA 2018 - VII Conference SOLINA Sustainable Development: Architecture - Building Construction - Environmental Engineering and Protection Innovative Energy-Efficient Technologies - Utilization of Renewable Energy Sources
|Number of page(s)||10|
|Published online||13 August 2018|
The use of discriminant analysis methods for diagnosis of the causes of differences in the properties of resin mortar containing various fillers
Rzeszow University of Technology, The Faculty of Civil and Environmental Engineering and Architecture, Poznanska 2, 35-082 Rzeszow, Poland
* Corresponding author: firstname.lastname@example.org
Resin mortars belong to the group of concrete-like construction composites. They are obtained by mixing a synthetic resin with a hardener and an appropriately selected aggregate. The latter component is usually as much as 90% of the composite mass and can largely shape the characteristics of the finished product. The fact that the type of filler used can significantly differentiate the values of physical and mechanical parameters of epoxy mortars is confirmed by the results of the exploratory data analysis method used in this article, which is discriminant analysis. This allows us to examine differences between groups of objects based on a set of selected independent variables (predictors). It is used to solve a wide range of classification and prediction problems. The core of discriminant analysis is a model presented in the form of a linear combination of independent variables, which allows classification of observations (e.g. test mortars) into one of the groups that are of interest to the researcher. In discriminant analysis one can distinguish the learning stage (model building), in which classification rules are created based on research results (training set) and the classification stage, i.e. the use of the model, e.g. for testing its prognostic accuracy.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.