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Volumn 65, Issue , 2013, Pages 352-358

Energy analysis of a building using artificial neural network: A review

Author keywords

Artificial neural networks; Building applications; Energy prediction

Indexed keywords

ALTERNATIVE TECHNOLOGIES; BUILDING APPLICATIONS; BUILDING SERVICES; DIVERSE APPLICATIONS; ENERGY ANALYSIS; ENERGY PREDICTION; HISTORY DATA; REGRESSION TECHNIQUES;

EID: 84880266711     PISSN: 03787788     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.enbuild.2013.06.007     Document Type: Review
Times cited : (257)

References (29)
  • 2
    • 0003176971 scopus 로고
    • Artificial neural network demonstration for automated generation of energy use predictors for commercial buildings
    • J.F. Kreider, and X.A. Wan Artificial neural network demonstration for automated generation of energy use predictors for commercial buildings ASHRAE Transactions 97 2 1991 775 779
    • (1991) ASHRAE Transactions , vol.97 , Issue.2 , pp. 775-779
    • Kreider, J.F.1    Wan, X.A.2
  • 3
    • 0027211515 scopus 로고
    • Application of neural networking models to predict energy use
    • Paper No. 3672
    • M. Anstett, and J.F. Kreider Application of neural networking models to predict energy use ASHRAE Transactions 1992 505 517 Paper No. 3672
    • (1992) ASHRAE Transactions , pp. 505-517
    • Anstett, M.1    Kreider, J.F.2
  • 4
    • 0028695610 scopus 로고
    • Using artificial neural networks to predict building energy parameters
    • Paper No. OR-94-17-4
    • W.J. Stevenson Using artificial neural networks to predict building energy parameters ASHRAE Transactions 100 2 1994 Paper No. OR-94-17-4
    • (1994) ASHRAE Transactions , vol.100 , Issue.2
    • Stevenson, W.J.1
  • 7
    • 0027211515 scopus 로고
    • Application of neural networking models to predict energy use
    • M. Ansett, and J.F. Kreider Application of neural networking models to predict energy use ASHRAE Transactions: Research 99 1 1993 505 517 (Pubitemid 23685690)
    • (1993) ASHRAE Transactions , vol.99 , Issue.PART 1 , pp. 505-517
    • Anstett, M.1    Kreider, J.F.2
  • 10
    • 0029356977 scopus 로고
    • Building energy use prediction and system identification using recurrent networks, transactions of the ASME
    • J.F. Kreider, D.E. Claridge, P. Curtiss, J.S. Haberl, and M. Krarti Building energy use prediction and system identification using recurrent networks, transactions of the ASME Journal of Solar Energy Engineering 117 1995 161 166
    • (1995) Journal of Solar Energy Engineering , vol.117 , pp. 161-166
    • Kreider, J.F.1    Claridge, D.E.2    Curtiss, P.3    Haberl, J.S.4    Krarti, M.5
  • 11
    • 0030313672 scopus 로고    scopus 로고
    • Great energy predictor shootout II: A Bayesian nonlinear regression with multiple hyper-parameters
    • Y. Chonan, K. Nishida, and T. Matsumoto Great energy predictor shootout II: a Bayesian nonlinear regression with multiple hyper-parameters ASHRAE Transactions: Symposia SA-96-3-1 1996 405 411
    • (1996) ASHRAE Transactions: Symposia SA-96-3-1 , pp. 405-411
    • Chonan, Y.1    Nishida, K.2    Matsumoto, T.3
  • 13
    • 0031368671 scopus 로고    scopus 로고
    • Examples of neural networks used for building system control and energy management
    • P.S. Curtiss Examples of neural networks used for building system control and energy management ASHRAE Transactions: Symposia BN 97-16-1 1996 909 913
    • (1996) ASHRAE Transactions: Symposia BN 97-16-1 , pp. 909-913
    • Curtiss, P.S.1
  • 14
    • 0034461103 scopus 로고    scopus 로고
    • Development of generalized neural network model to detect faults in building energy performance - Part I, part II
    • M.R.B. Breekweg, P. Gruber, and O. Ahmed Development of generalized neural network model to detect faults in building energy performance - part I, part II ASHRAE Transactions: Research 4372 2000 61 93
    • (2000) ASHRAE Transactions: Research , vol.4372 , pp. 61-93
    • Breekweg, M.R.B.1    Gruber, P.2    Ahmed, O.3
  • 15
    • 24944577137 scopus 로고    scopus 로고
    • Artificial neural networks applications in building energy predictions and a case study for tropical climates
    • DOI 10.1002/er.1105
    • M. Yalcintas, and S. Akkurt Artificial neural networks applications in building energy predictions and a case study for tropical climates International Journal of Energy Research 29 2005 891 901 (Pubitemid 41300340)
    • (2005) International Journal of Energy Research , vol.29 , Issue.10 , pp. 891-901
    • Yalcintas, M.1    Akkurt, S.2
  • 16
    • 52349093047 scopus 로고    scopus 로고
    • Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption
    • A.H. Neto, and F.A.S. Floreth Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption Energy and Buildings 40 12 2008 2169 2176
    • (2008) Energy and Buildings , vol.40 , Issue.12 , pp. 2169-2176
    • Neto, A.H.1    Floreth, F.A.S.2
  • 17
    • 79953166847 scopus 로고    scopus 로고
    • Analysis of a residential building energy consumption demand model
    • W. Yu, B. Li, Y. Lei, and M. Liu Analysis of a residential building energy consumption demand model Energies 4 2011 475 487
    • (2011) Energies , vol.4 , pp. 475-487
    • Yu, W.1    Li, B.2    Lei, Y.3    Liu, M.4
  • 20
    • 1642323621 scopus 로고    scopus 로고
    • Cooling load prediction for buildings using general regression neural networks
    • A.E. Ben Nakhi, and M.A. Mahmood Cooling load prediction for buildings using general regression neural networks Energy Conversion and Management 45 13-14 2004 2127 2141
    • (2004) Energy Conversion and Management , vol.45 , Issue.1314 , pp. 2127-2141
    • Ben Nakhi, A.E.1    Mahmood, M.A.2
  • 21
    • 2342635095 scopus 로고    scopus 로고
    • A comparison of linear and neural network ARX models applied to a prediction of the indoor temperature of a building
    • DOI 10.1007/s00521-004-0401-8
    • A. Mechaqrane, and M. Zouak A comparison of linear and neural network ARX models applied to a prediction of the indoor temperature of a building Neural Computing and Applications 13 1 2004 32 37 (Pubitemid 38604228)
    • (2004) Neural Computing and Applications , vol.13 , Issue.1 , pp. 32-37
    • Mechaqrane, A.1    Zouak, M.2
  • 22
    • 2642538304 scopus 로고    scopus 로고
    • Modeling of the space and domestic hot-water heating energy-consumption in the residential sector using neural networks
    • DOI 10.1016/j.apenergy.2003.12.006, PII S0306261903002344
    • M. Aydinalp, V.I. Ugursal, and A.S. Fung Modelling of the space and domestic hot water heating energy consumption in the residential sector using neural networks" Applied Energy 79 2 2004 159 178 (Pubitemid 38728822)
    • (2004) Applied Energy , vol.79 , Issue.2 , pp. 159-178
    • Aydinalp, M.1    Ugursal, V.I.2    Fung, A.S.3
  • 23
    • 0036680681 scopus 로고    scopus 로고
    • On the energy consumption in residential buildings
    • DOI 10.1016/S0378-7788(01)00137-2, PII S0378778801001372
    • G. Michalakakou, M. Santamouris, and A. Tssgrassoulis On the energy consumption in residential buildings Energy and Buildings 34 7 2002 727 736 (Pubitemid 34532366)
    • (2002) Energy and Buildings , vol.34 , Issue.7 , pp. 727-736
    • Mihalakakou, G.1    Santamouris, M.2    Tsangrassoulis, A.3
  • 25
    • 0038238083 scopus 로고    scopus 로고
    • Application of artificial neural network to predict the optimal start time for heating system in building
    • I. Yang, M. Yeo, and K. Kim Application of artificial neural network to predict the optimal start time for heating system in building Energy Conversion and Management 44 17 2003 2791 2809
    • (2003) Energy Conversion and Management , vol.44 , Issue.17 , pp. 2791-2809
    • Yang, I.1    Yeo, M.2    Kim, K.3
  • 26
    • 0242317861 scopus 로고    scopus 로고
    • Subsystem level fault diagnosis of a building's air-handling unit using general regression neural networks
    • DOI 10.1016/S0306-2619(03)00107-7
    • W. Lee, J.M. House, and N. Kyong Subsystem level fault diagnosis of a building's air-handling unit using general regression neural networks Applied Energy 77 2 2004 153 170 (Pubitemid 37348234)
    • (2004) Applied Energy , vol.77 , Issue.2 , pp. 153-170
    • Lee, W.-Y.1    House, J.M.2    Kyong, N.-H.3
  • 27
    • 0036758568 scopus 로고    scopus 로고
    • Energy conservation in buildings through efficient A/C control using neural networks
    • DOI 10.1016/S0306-2619(02)00027-2, PII S0306261902000272
    • A.E. Ben-Nakhi, and M.A. Mahmound Energy conservation in buildings through efficient A/C control using neural networks Applied Energy 73 1 2002 5 23 (Pubitemid 35381365)
    • (2002) Applied Energy , vol.73 , Issue.1 , pp. 5-23
    • Ben-Nakhi, A.E.1    Mahmoud, M.A.2
  • 28
    • 0036983779 scopus 로고    scopus 로고
    • Application of artificial neural network for modelling the thermal dynamics of a building's space and its heating system
    • M.M. Gouda, S. Danaher, and C.U. Underwood Application of artificial neural network for modelling the thermal dynamics of a building's space and its heating system Mathematical and Computer Modelling of Dynamical Systems 8 3 2010 333 344
    • (2010) Mathematical and Computer Modelling of Dynamical Systems , vol.8 , Issue.3 , pp. 333-344
    • Gouda, M.M.1    Danaher, S.2    Underwood, C.U.3
  • 29
    • 0036734689 scopus 로고    scopus 로고
    • Prediction of the COP of existing rooftop units using artificial neural networks and minimum number of sensors
    • R. Zmeureanu Prediction of the COP of existing rooftop units using artificial neural networks and minimum number of sensors Energy 27 9 2002 889 904
    • (2002) Energy , vol.27 , Issue.9 , pp. 889-904
    • Zmeureanu, R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.