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Volumn 30, Issue 14, 2006, Pages 1158-1174

An energy benchmarking model based on artificial neural network method with a case example for tropical climates

Author keywords

Artificial neural network; Buildings; Energy benchmarking; Energy conservation

Indexed keywords

BENCHMARKING; BUILDINGS; COMPUTER SIMULATION; ENERGY UTILIZATION; NEURAL NETWORKS;

EID: 33751034448     PISSN: 0363907X     EISSN: 1099114X     Source Type: Journal    
DOI: 10.1002/er.1212     Document Type: Article
Times cited : (58)

References (10)
  • 1
    • 0036497459 scopus 로고    scopus 로고
    • Model-based benchmarking with applications to laboratory buildings
    • Federspiel C, Zhang Q, Arens E. 2002. Model-based benchmarking with applications to laboratory buildings. Energy and Buildings 34(3):203-214.
    • (2002) Energy and Buildings , vol.34 , Issue.3 , pp. 203-214
    • Federspiel, C.1    Zhang, Q.2    Arens, E.3
  • 4
    • 24744438428 scopus 로고    scopus 로고
    • Development of California commercial building energy benchmarking database
    • Kinney S, Piette MA. 2002. Development of California commercial building energy benchmarking database. Information and Electronic Technologies, vol. 7, 109-120.
    • (2002) Information and Electronic Technologies , vol.7 , pp. 109-120
    • Kinney, S.1    Piette, M.A.2
  • 6
    • 33847766017 scopus 로고    scopus 로고
    • Review of California and national methods for energy-performance benchmarking for commercial buildings
    • California Energy Commission, Public Interest Energy Research Program, LBNL No. 57364
    • Matson N, Piette MA. 2005. Review of California and national methods for energy-performance benchmarking for commercial buildings. California Energy Commission, Public Interest Energy Research Program, LBNL No. 57364.
    • (2005)
    • Matson, N.1    Piette, M.A.2
  • 9
    • 24944577137 scopus 로고    scopus 로고
    • Artificial neural networks applications in building energy predictions and a case study for tropical climates
    • Yalcintas M, Akkurt S. 2005. Artificial neural networks applications in building energy predictions and a case study for tropical climates. International Journal of Energy Research 29:891-901.
    • (2005) International Journal of Energy Research , vol.29 , pp. 891-901
    • Yalcintas, M.1    Akkurt, S.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.