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Application of Data Mining Techniques in the Analysis of Indoor Hygrothermal Conditions

Part of the book series: SpringerBriefs in Applied Sciences and Technology ((BRIEFSAPPLSCIENCES))

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Abstract

This chapter presents the main conclusions, stressing how descriptive statistics combined with multivariate analysis can be applied to a specific case study.

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Authors and Affiliations

  1. Department of Civil Engineering, University of Porto, Porto, Portugal

    Nuno M. M. Ramos

  2. Department of Civil Engineering, University of Porto, Porto, Portugal

    João M. P. Q. Delgado

  3. Department of Civil Engineering, Polytechnic Institute of Viseu, Viseu, Portugal

    Ricardo M. S. F. Almeida

  4. Department of Civil Engineering, University of Porto, Porto, Portugal

    Maria L. Simões

  5. Department of Civil Engineering, University of Porto, Porto, Portugal

    Sofia Manuel

Authors
  1. Nuno M. M. Ramos
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  2. João M. P. Q. Delgado
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  3. Ricardo M. S. F. Almeida
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  4. Maria L. Simões
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  5. Sofia Manuel
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Corresponding author

Correspondence to Nuno M. M. Ramos .

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Ramos, N.M.M., Delgado, J.M.P.Q., Almeida, R.M.S.F., Simões, M.L., Manuel, S. (2016). Conclusions. In: Application of Data Mining Techniques in the Analysis of Indoor Hygrothermal Conditions. SpringerBriefs in Applied Sciences and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-22294-3_6

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  • DOI: https://doi.org/10.1007/978-3-319-22294-3_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22293-6

  • Online ISBN: 978-3-319-22294-3

  • eBook Packages: EngineeringEngineering (R0)

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