메뉴 건너뛰기




Volumn 53, Issue 3, 2010, Pages 871-881

Prediction of indoor climate and long-term air quality using the BTA-AQP model: Part II. Overall model evaluation and application

Author keywords

Air quality predictive model; Long term mean; Modeling; Typical meteorological year

Indexed keywords

AIR QUALITY DATA; AIR QUALITY TRENDS; BIAS ERROR; DATA SETS; GAS CONCENTRATION; GRAPHICAL PRESENTATIONS; INDOOR CLIMATE; MODEL PERFORMANCE; MODELING; OVERALL-MODEL; PREDICTION ERRORS; PREDICTIVE MODELS; THERMAL ANALYSIS; TYPICAL METEOROLOGICAL YEAR; WEATHER DATA;

EID: 77954104675     PISSN: 21510032     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (5)

References (14)
  • 1
    • 2342567076 scopus 로고    scopus 로고
    • A literature review of swine heat and moisture production
    • Brown-Brandl, T. M., J. A. Nienaber, H. Xin, and R. S. Gates. 2004. A literature review of swine heat and moisture production. Trans. ASAE 47(1):259-270.
    • (2004) Trans. ASAE , vol.47 , Issue.1 , pp. 259-270
    • Brown-Brandl, T.M.1    Nienaber, J.A.2    Xin, H.3    Gates, R.S.4
  • 3
    • 31044433834 scopus 로고    scopus 로고
    • Artificial neural network models for prediction of PM10 hourly concentrations in the greater area of Athens, Greece
    • Grivas, G., and A. Chaloulakou. 2006. Artificial neural network models for prediction of PM10 hourly concentrations in the greater area of Athens, Greece. Atmos. Environ. 40(7):1216-1229.
    • (2006) Atmos. Environ. , vol.40 , Issue.7 , pp. 1216-1229
    • Grivas, G.1    Chaloulakou, A.2
  • 7
    • 19544377320 scopus 로고    scopus 로고
    • A neural network forecast for daily average PM10 concentrations in Belgium
    • Hooyberghs, J., C. Mensink, G. Dumont, F. Fierens, and O. Brasseur. 2005. A neural network forecast for daily average PM10 concentrations in Belgium. Atmos. Environ. 39(18):3279-3289.
    • (2005) Atmos. Environ. , vol.39 , Issue.18 , pp. 3279-3289
    • Hooyberghs, J.1    Mensink, C.2    Dumont, G.3    Fierens, F.4    Brasseur, O.5
  • 9
    • 72149099601 scopus 로고    scopus 로고
    • NSRDB, Golden, Co: National Renewable Energy Laboratory
    • NSRDB. 2008. Users Manual for TMY3 Data Sets. Golden, Co: National Renewable Energy Laboratory.
    • (2008) Users Manual for TMY3 Data Sets
  • 10
    • 33751426966 scopus 로고    scopus 로고
    • Use of different methodologies for thermal load and energy estimations in buildings including meteorological and sociological parameters
    • Pedersen, L. 2007. Use of different methodologies for thermal load and energy estimations in buildings including meteorological and sociological parameters. Renewable and Sustainable Energy Review 11(5):998-1007.
    • (2007) Renewable and Sustainable Energy Review , vol.11 , Issue.5 , pp. 998-1007
    • Pedersen, L.1
  • 11
    • 33749247555 scopus 로고    scopus 로고
    • Multiple linear regression and artificial neural network based on principal components to predict ozone concentrations
    • Sousa, S. I. V., F. G. Martins, M. C. M. Alvim-Ferraz, and M. C. Pereira. 2007. Multiple linear regression and artificial neural network based on principal components to predict ozone concentrations. Environ. Modeling and Software 22(1):97-103.
    • (2007) Environ. Modeling and Software , vol.22 , Issue.1 , pp. 97-103
    • Sousa, S.I.V.1    Martins, F.G.2    Alvim-Ferraz, M.C.M.3    Pereira, M.C.4
  • 12
    • 77954126682 scopus 로고    scopus 로고
    • Prediction of indoor climate and long-term air quality using the BTA-AQP model: Part I. BTA model development and evaluation
    • Sun, G., and S. J. Hoff. 2010. Prediction of indoor climate and long-term air quality using the BTA-AQP model: Part I. BTA model development and evaluation. Trans. ASABE 53(3):863-870.
    • (2010) Trans. ASABE , vol.53 , Issue.3 , pp. 863-870
    • Sun, G.1    Hoff, S.J.2
  • 13
    • 44449122355 scopus 로고    scopus 로고
    • Development and comparison of backpropagation and generalized regression neural network models to predict diurnal and seasonal gas and PM10 concentrations and emissions from swine buildings
    • Sun, G., S. J. Hoff, B. C. Zelle, and M. A. Nelson. 2008. Development and comparison of backpropagation and generalized regression neural network models to predict diurnal and seasonal gas and PM10 concentrations and emissions from swine buildings. Trans. ASABE 51(2):685-694.
    • (2008) Trans. ASABE , vol.51 , Issue.2 , pp. 685-694
    • Sun, G.1    Hoff, S.J.2    Zelle, B.C.3    Nelson, M.A.4
  • 14
    • 35848937340 scopus 로고    scopus 로고
    • Building energy simulation using multi-years and typical meteorological years in different climates
    • Yang, L., J. C. Lam, J. Liu, and C. L. Tsang. 2008. Building energy simulation using multi-years and typical meteorological years in different climates. Energy Convers. and Mgmt. 49(1):113-124.
    • (2008) Energy Convers. and Mgmt , vol.49 , Issue.1 , pp. 113-124
    • Yang, L.1    Lam, J.C.2    Liu, J.3    Tsang, C.L.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.