Publication

Regression Analysis of Building Energy Demand

2015
Student Projects

Abstract

This project attempts to tackle the problem of analysing the heat demand of build- ings at a large (district or city) scale. Specifically, building data from Geneva is used as a case study while building an environment with suitable tools for a continued analysis. Detailed modelling of these systems is limited greatly by not only com- putational resources, but also by data availability. Meta-modelling is a potential technique to overcome these issues, and the first steps towards this are analysis of available data and parameter interactions, as well as identification of key influence parameters, through the use of stepwise regression techniques. A set of tools to accomplish these goals is introduced, and then used to perform an initial analysis.

Official source

https://infoscience.epfl.ch/entities/publication/5079affd-74b0-47a3-87fe-d043c1ba61ac

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2015
Student Projects

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/5079affd-74b0-47a3-87fe-d043c1ba61ac

About this result

Related concepts (32)

Regression analysis

In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called the 'outcome' or 'response' variable, or a 'label' in machine learning parlance) and one or more independent variables (often called 'predictors', 'covariates', 'explanatory variables' or 'features'). The most common form of regression analysis is linear regression, in which one finds the line (or a more complex linear combination) that most closely fits the data according to a specific mathematical criterion.

Data analysis

Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively.

Linear regression

In statistics, linear regression is a linear approach for modelling the relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables). The case of one explanatory variable is called simple linear regression; for more than one, the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable.

Related publications (30)

Regression Analysis of Building Energy Demand

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