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Energy performance assessment of campus buildings using data mining technologies
作者:
Kehua Li
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uow.edu.au
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参考文章
(32)
1.
Cheng Fan, Fu Xiao, Shengwei Wang, None,
Rare Event Analysis of High Dimensional Building Operational Data Using Data Mining Techniques
2014 Purdue Conferences. 3rd International High Performance Buildings Conference at Purdue..
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Classification and regression trees
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James A. Davis, Darin W. Nutter,
Occupancy diversity factors for common university building types
Energy and Buildings.
,vol. 42, pp. 1543- 1551 ,(2010) ,
10.1016/J.ENBUILD.2010.03.025
4.
Ammar Ahmed, Nicholas E. Korres, Joern Ploennigs, Haithum Elhadi, Karsten Menzel,
Mining building performance data for energy-efficient operation
Advanced Engineering Informatics.
,vol. 25, pp. 341- 354 ,(2011) ,
10.1016/J.AEI.2010.10.002
5.
William Chung,
Review of building energy-use performance benchmarking methodologies
Applied Energy.
,vol. 88, pp. 1470- 1479 ,(2011) ,
10.1016/J.APENERGY.2010.11.022
6.
Cheng Fan, Fu Xiao, Chengchu Yan,
A framework for knowledge discovery in massive building automation data and its application in building diagnostics
Automation in Construction.
,vol. 50, pp. 81- 90 ,(2015) ,
10.1016/J.AUTCON.2014.12.006
7.
Mehmet Aksoezen, Magdalena Daniel, Uta Hassler, Niklaus Kohler,
Building age as an indicator for energy consumption
Energy and Buildings.
,vol. 87, pp. 74- 86 ,(2015) ,
10.1016/J.ENBUILD.2014.10.074
8.
Charles Bouveyron, Camille Brunet-Saumard,
Model-based clustering of high-dimensional data: A review
Computational Statistics & Data Analysis.
,vol. 71, pp. 52- 78 ,(2014) ,
10.1016/J.CSDA.2012.12.008
9.
Roger K. Blashfield,
Mixture model tests of cluster analysis: Accuracy of four agglomerative hierarchical methods.
Psychological Bulletin.
,vol. 83, pp. 377- 388 ,(1976) ,
10.1037/0033-2909.83.3.377
10.
William Chung,
Using the fuzzy linear regression method to benchmark the energy efficiency of commercial buildings
Applied Energy.
,vol. 95, pp. 45- 49 ,(2012) ,
10.1016/J.APENERGY.2012.01.061
来源期刊
2020 年,
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