Regression model for heat consumption monitoring and forecasting

Heat supply is socially and economically important in our country. In this regard, high-quality monitoring and planning of the development of heat supply systems are a strategic vector of scientific research. This paper is focused on the studies demonstrating how to choose a methodological approach...

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Main Authors: Dobrovolskaya Tatyana, Stennikov Valery
Format: Article
Language:English
Published: EDP Sciences 2018-01-01
Series:E3S Web of Conferences
Online Access:https://doi.org/10.1051/e3sconf/20183903005
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author Dobrovolskaya Tatyana
Stennikov Valery
author_facet Dobrovolskaya Tatyana
Stennikov Valery
author_sort Dobrovolskaya Tatyana
collection DOAJ
description Heat supply is socially and economically important in our country. In this regard, high-quality monitoring and planning of the development of heat supply systems are a strategic vector of scientific research. This paper is focused on the studies demonstrating how to choose a methodological approach to describe changes in heat consumption in the retrospective. The change in heat consumption is described using multiple regression models. In the first part of the paper, the parameters for the regression model are determined and a statistical analysis of the obtained model is performed. In the second part of the paper, to eliminate the multicollinearity of the regression equation, the number of dependent variables in the model is reduced. A statistical analysis of the new regression model and the exponential regression model are carried out. The heat consumption values obtained using these models are compared with the statistical data. The conclusions about the quality of the obtained regression models are made. In the third part of the article, we make a forecast of heat consumption in the medium term by using a linear regression model and an exponential model.
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spelling doaj.art-27761d83603e452282df10ae38f597c12022-12-21T17:14:38ZengEDP SciencesE3S Web of Conferences2267-12422018-01-01390300510.1051/e3sconf/20183903005e3sconf_mmmaosdphs2018_03005Regression model for heat consumption monitoring and forecastingDobrovolskaya TatyanaStennikov ValeryHeat supply is socially and economically important in our country. In this regard, high-quality monitoring and planning of the development of heat supply systems are a strategic vector of scientific research. This paper is focused on the studies demonstrating how to choose a methodological approach to describe changes in heat consumption in the retrospective. The change in heat consumption is described using multiple regression models. In the first part of the paper, the parameters for the regression model are determined and a statistical analysis of the obtained model is performed. In the second part of the paper, to eliminate the multicollinearity of the regression equation, the number of dependent variables in the model is reduced. A statistical analysis of the new regression model and the exponential regression model are carried out. The heat consumption values obtained using these models are compared with the statistical data. The conclusions about the quality of the obtained regression models are made. In the third part of the article, we make a forecast of heat consumption in the medium term by using a linear regression model and an exponential model.https://doi.org/10.1051/e3sconf/20183903005
spellingShingle Dobrovolskaya Tatyana
Stennikov Valery
Regression model for heat consumption monitoring and forecasting
E3S Web of Conferences
title Regression model for heat consumption monitoring and forecasting
title_full Regression model for heat consumption monitoring and forecasting
title_fullStr Regression model for heat consumption monitoring and forecasting
title_full_unstemmed Regression model for heat consumption monitoring and forecasting
title_short Regression model for heat consumption monitoring and forecasting
title_sort regression model for heat consumption monitoring and forecasting
url https://doi.org/10.1051/e3sconf/20183903005
work_keys_str_mv AT dobrovolskayatatyana regressionmodelforheatconsumptionmonitoringandforecasting
AT stennikovvalery regressionmodelforheatconsumptionmonitoringandforecasting