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Application of data mining techniques for building simulation performance prediction

Morbitzer, C., Strachan, P. and Simpson, C.
2003
Eighth International IBPSA Conference, Eindhoven, Netherlands, August 11-14, 2003


Morbitzer, C., Strachan, P. and Simpson, C., (2003), "Application of data mining techniques for building simulation performance prediction", Eighth International IBPSA Conference, Eindhoven, Netherlands, August 11-14, 2003.
Abstract:
Simulation exercises covering long periods (e.g.. annual simulations) can produce large quantities of data. The result data set is often primarily used to determine key performance parameters such as the frequency binning of internal temperatures. Efforts to obtain an understanding for reasons behind the predicted building performance are often only carried out to a limited extent and simulation is therefore not used to its full potential. This paper describes how data mining can be used to enhance the analysis of results obtained from a simulation exercise. It identifies clustering as a particular useful analysis technique and illustrates its potential in enhancing the analysis of building simulation performance predictions.

This publication in whole or part may be found online at: This link was broken when checked on Dec. 2006here.

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Author Information and Other Publications Notes
Morbitzer, C.
HLM Design, Glasgow, United Kingdom, email cmorbitzer@hlm.co.uk
  1. Towards the Integration of Simulation into the Building Design Process  
Strachan, P.
Building Simulation, Wiltshire, United Kingdom, email cathie@buildingsimulation.co.uk
  1. Building-integrated photovoltaic and thermal applications in a subtropical hotel building
  2. Practical application of uncertainty analysis
  3. Simulation support for performance assessment of building components  
Simpson, C.
Energy Systems Research Unit (ESRU), University of Strathclyde, Glasgow, United Kingdom, email paul@esru.strath.ac
     



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