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Multiple Linear Regressions

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Part of the book series: SpringerBriefs in Energy ((BRIEFSENERGY))

Abstract

This chapter intends to develop a mathematical model that allows predicting, with an acceptable degree of uncertainty, the energy consumption and CO2 emissions for the office buildings in Chile. Through the multivariable regression method, diverse equations will be produced that will bear in mind the parameters mentioned for the different locations. In this way, the designers will be able to know the consequences that their decisions will have on the energy consumption and CO2 emissions. This research has an eminently practical nature and is susceptible to being applied in the future design and construction of buildings.

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Correspondence to Carlos Rubio-Bellido .

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Rubio-Bellido, C., Pérez-Fargallo, A., Pulido-Arcas, J. (2018). Multiple Linear Regressions. In: Energy Optimization and Prediction in Office Buildings. SpringerBriefs in Energy. Springer, Cham. https://doi.org/10.1007/978-3-319-90146-6_4

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  • DOI: https://doi.org/10.1007/978-3-319-90146-6_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-90145-9

  • Online ISBN: 978-3-319-90146-6

  • eBook Packages: EnergyEnergy (R0)

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