메뉴 건너뛰기




Volumn 109, Issue , 2015, Pages 144-151

Early prediction of the performance of green building projects using pre-project planning variables: Data mining approaches

Author keywords

Certified green building; Cost performance; Data mining; Green building project; Pre project planning; Schedule performance

Indexed keywords

BACKPROPAGATION; BACKPROPAGATION ALGORITHMS; BUILDINGS; COSTS; DECISION TREES; FORECASTING; NEURAL NETWORKS; SUPPORT VECTOR MACHINES; TREES (MATHEMATICS);

EID: 84923342424     PISSN: 09596526     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jclepro.2014.08.071     Document Type: Article
Times cited : (50)

References (64)
  • 1
    • 32444446490 scopus 로고    scopus 로고
    • Automated neonatal seizure detection: A multistage classification system through feature selection based on relevance and redundancy analysis
    • A. Aarabi, F. Wallois, and R. Grebe Automated neonatal seizure detection: a multistage classification system through feature selection based on relevance and redundancy analysis Clin. Neurophysiol. 117 2006 328 340
    • (2006) Clin. Neurophysiol. , vol.117 , pp. 328-340
    • Aarabi, A.1    Wallois, F.2    Grebe, R.3
  • 2
    • 56349089940 scopus 로고    scopus 로고
    • Support vector machines combined with feature selection for breast cancer diagnosis
    • M.F. Akay Support vector machines combined with feature selection for breast cancer diagnosis Expert Syst. Appl. 36 2009 3240 3247
    • (2009) Expert Syst. Appl. , vol.36 , pp. 3240-3247
    • Akay, M.F.1
  • 3
    • 30344483921 scopus 로고    scopus 로고
    • On learning algorithm selection for classification
    • S. Ali, and K.A. Smith On learning algorithm selection for classification Appl. Soft Comput. 6 2006 119 138
    • (2006) Appl. Soft Comput. , vol.6 , pp. 119-138
    • Ali, S.1    Smith, K.A.2
  • 4
    • 34147111649 scopus 로고    scopus 로고
    • Fast cross-validation algorithms for least squares support vector machine and kernel ridge regression
    • S. An, W. Liu, and S. Venkatesh Fast cross-validation algorithms for least squares support vector machine and kernel ridge regression Pattern Recogn. 40 2007 2154 2162
    • (2007) Pattern Recogn. , vol.40 , pp. 2154-2162
    • An, S.1    Liu, W.2    Venkatesh, S.3
  • 5
    • 79951552114 scopus 로고    scopus 로고
    • Selecting safer building products in practice
    • J. Atlee Selecting safer building products in practice J. Clean. Prod. 19 2011 459 463
    • (2011) J. Clean. Prod. , vol.19 , pp. 459-463
    • Atlee, J.1
  • 6
    • 84864953124 scopus 로고    scopus 로고
    • Landslide susceptibility assessment in Vietnam using support vector machines, decision tree, and naïve bayes models
    • D.T. Bui, B. Pradhan, O. Lofman, and I. Revhaug Landslide susceptibility assessment in Vietnam using support vector machines, decision tree, and naïve bayes models Math. Probl. Eng. 2012 2012 1 26
    • (2012) Math. Probl. Eng. , vol.2012 , pp. 1-26
    • Bui, D.T.1    Pradhan, B.2    Lofman, O.3    Revhaug, I.4
  • 7
    • 77949658813 scopus 로고    scopus 로고
    • Application of relevance vector machine and logistic regression for machine degradation assessment
    • W. Caesarendra, A. Widodo, and B.-S. Yang Application of relevance vector machine and logistic regression for machine degradation assessment Mech. Syst. Signal Process. 24 2010 1161 1171
    • (2010) Mech. Syst. Signal Process. , vol.24 , pp. 1161-1171
    • Caesarendra, W.1    Widodo, A.2    Yang, B.-S.3
  • 10
    • 83555179186 scopus 로고    scopus 로고
    • Selection of effective features for ECG beat recognition based on nonlinear correlations
    • Y.-H. Chen, and S.-N. Yu Selection of effective features for ECG beat recognition based on nonlinear correlations Artif. Intell. Med. 54 2012 43 52
    • (2012) Artif. Intell. Med. , vol.54 , pp. 43-52
    • Chen, Y.-H.1    Yu, S.-N.2
  • 11
    • 0035581097 scopus 로고    scopus 로고
    • Building project scope definition using project definition rating index
    • C.-S. Cho, and G.E. Gibson Jr. Building project scope definition using project definition rating index J. Archit. Eng. 7 2001 115 125
    • (2001) J. Archit. Eng. , vol.7 , pp. 115-125
    • Cho, C.-S.1    Gibson, G.E.2
  • 12
    • 0004326740 scopus 로고    scopus 로고
    • Construction Industry Institute (cii) Implementation Resource 155-2, Austin, TX
    • Construction Industry Institute (CII) Project Definition Rating Index (PDRI) - Building Projects Implementation Resource 155-2, Austin, TX 1999
    • (1999) Project Definition Rating Index (PDRI) - Building Projects
  • 13
    • 0024861871 scopus 로고
    • Approximation by superpositions of a sigmoidal function
    • G. Cybenko Approximation by superpositions of a sigmoidal function Math. Control Signal 2 1989 303 314
    • (1989) Math. Control Signal , vol.2 , pp. 303-314
    • Cybenko, G.1
  • 14
    • 19344364327 scopus 로고    scopus 로고
    • Predicting breast cancer survivability: A comparison of three data mining methods
    • D. Delen, G. Walker, and A. Kadam Predicting breast cancer survivability: a comparison of three data mining methods Artif. Intell. Med. 34 2005 113 127
    • (2005) Artif. Intell. Med. , vol.34 , pp. 113-127
    • Delen, D.1    Walker, G.2    Kadam, A.3
  • 15
    • 38649138750 scopus 로고    scopus 로고
    • Forecasting financial condition of Chinese listed companies based on support vector machine
    • Y. Ding, X. Song, and Y. Zen Forecasting financial condition of Chinese listed companies based on support vector machine Expert Syst. Appl. 34 2008 3081 3089
    • (2008) Expert Syst. Appl. , vol.34 , pp. 3081-3089
    • Ding, Y.1    Song, X.2    Zen, Y.3
  • 18
    • 84878501878 scopus 로고    scopus 로고
    • Model-supported business-to-business prospect prediction based on an iterative customer acquisition framework
    • J. D'Haen, and D. van den Poel Model-supported business-to-business prospect prediction based on an iterative customer acquisition framework Ind. Mark. Manag. 42 2013 544 551
    • (2013) Ind. Mark. Manag. , vol.42 , pp. 544-551
    • D'Haen, J.1    Van Den Poel, D.2
  • 19
    • 60849127572 scopus 로고    scopus 로고
    • Hierarchical fuzzy rule based classification systems with genetic rule selection for imbalanced data-sets
    • A. Fernández, M.J. del Jesus, and F. Herrera Hierarchical fuzzy rule based classification systems with genetic rule selection for imbalanced data-sets Int. J. Approx. Reason 50 2009 561 577
    • (2009) Int. J. Approx. Reason , vol.50 , pp. 561-577
    • Fernández, A.1    Del Jesus, M.J.2    Herrera, F.3
  • 20
    • 80052951934 scopus 로고    scopus 로고
    • A combined SMOTE and PSO based RBF classifier for two-class imbalanced problems
    • M. Gao, X. Hong, S. Chen, and C.J. Harris A combined SMOTE and PSO based RBF classifier for two-class imbalanced problems Neurocomputing 74 2011 3456 3466
    • (2011) Neurocomputing , vol.74 , pp. 3456-3466
    • Gao, M.1    Hong, X.2    Chen, S.3    Harris, C.J.4
  • 21
    • 0032146239 scopus 로고    scopus 로고
    • Artificial neural networks (the multilayer perceptron) - A review of applications in the atmospheric sciences
    • M.W. Gardner, and S.R. Dorling Artificial neural networks (the multilayer perceptron) - A review of applications in the atmospheric sciences Atmos. Environ. 32 1998 2627 2636
    • (1998) Atmos. Environ. , vol.32 , pp. 2627-2636
    • Gardner, M.W.1    Dorling, S.R.2
  • 22
    • 84856265945 scopus 로고    scopus 로고
    • Identification of motion from multi-channel EMG signals for control of prosthetic hand
    • P. Geethanjali, and K.K. Ray Identification of motion from multi-channel EMG signals for control of prosthetic hand Australas. Phys. Eng. Sci. Med. 34 2011 419 427
    • (2011) Australas. Phys. Eng. Sci. Med. , vol.34 , pp. 419-427
    • Geethanjali, P.1    Ray, K.K.2
  • 26
    • 84885007765 scopus 로고    scopus 로고
    • Comparison of schedule delay and causal factors between traditional and green construction projects
    • B.-G. Hwang, and L.P. Leong Comparison of schedule delay and causal factors between traditional and green construction projects Technol. Econ. Dev. Eco. 19 2013 310 330
    • (2013) Technol. Econ. Dev. Eco. , vol.19 , pp. 310-330
    • Hwang, B.-G.1    Leong, L.P.2
  • 30
    • 0031381525 scopus 로고    scopus 로고
    • Wrappers for feature subset selection
    • R. Kohavi, and G.H. John Wrappers for feature subset selection Artif. Intell. 97 1997 273 324
    • (1997) Artif. Intell. , vol.97 , pp. 273-324
    • Kohavi, R.1    John, G.H.2
  • 31
    • 7244248755 scopus 로고    scopus 로고
    • A comparative study of feature selection and multiclass classification methods for tissue classification based on gene expression
    • T. Li, C. Zhang, and M. Ogihara A comparative study of feature selection and multiclass classification methods for tissue classification based on gene expression Bioinformatic 20 2004 2429 2437
    • (2004) Bioinformatic , vol.20 , pp. 2429-2437
    • Li, T.1    Zhang, C.2    Ogihara, M.3
  • 32
    • 77952554315 scopus 로고    scopus 로고
    • A learning method for the class imbalance problem with medical data sets
    • D.-C. Li, C.-W. Liu, and S.C. Hu A learning method for the class imbalance problem with medical data sets Comput. Biol. Med. 40 2010 509 518
    • (2010) Comput. Biol. Med. , vol.40 , pp. 509-518
    • Li, D.-C.1    Liu, C.-W.2    Hu, S.C.3
  • 33
    • 0000865860 scopus 로고    scopus 로고
    • Some issues on scalable feature selection
    • H. Liu, and R. Setiono Some issues on scalable feature selection Expert Syst. Appl. 15 1998 333 339
    • (1998) Expert Syst. Appl. , vol.15 , pp. 333-339
    • Liu, H.1    Setiono, R.2
  • 34
    • 70349562484 scopus 로고    scopus 로고
    • OWA rough set model for forecasting the revenues growth rate of the electronic industry
    • J.-W. Liu, C.-H. Cheng, Y.-H. Chen, and T.-L. Chen OWA rough set model for forecasting the revenues growth rate of the electronic industry Expert Syst. Appl. 37 2010 610 617
    • (2010) Expert Syst. Appl. , vol.37 , pp. 610-617
    • Liu, J.-W.1    Cheng, C.-H.2    Chen, Y.-H.3    Chen, T.-L.4
  • 35
    • 44749088791 scopus 로고    scopus 로고
    • Prediction models of human plasma protein binding rate and oral bioavailability derived by using GA-CG-SVM method
    • C.-Y. Ma, S.-Y. Yang, H. Zhang, M.-L. Xiang, Q. Huang, and Y.-Q. Wei Prediction models of human plasma protein binding rate and oral bioavailability derived by using GA-CG-SVM method J. Pharm. Biomed. 47 2008 677 682
    • (2008) J. Pharm. Biomed. , vol.47 , pp. 677-682
    • Ma, C.-Y.1    Yang, S.-Y.2    Zhang, H.3    Xiang, M.-L.4    Huang, Q.5    Wei, Y.-Q.6
  • 37
    • 17844363481 scopus 로고    scopus 로고
    • Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters
    • J.H. Min, and Y.-C. Lee Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters Expert Syst. Appl. 28 2005 603 614
    • (2005) Expert Syst. Appl. , vol.28 , pp. 603-614
    • Min, J.H.1    Lee, Y.-C.2
  • 38
    • 49449083313 scopus 로고    scopus 로고
    • Feature selection using localized generalization error for supervised classification problems using RBFNN
    • W.W.Y. Ng, D.S. Yeung, M. Firth, E.C.C. Tsang, and X.-Z. Wang Feature selection using localized generalization error for supervised classification problems using RBFNN Pattern Recogn. 41 2008 3706 3719
    • (2008) Pattern Recogn. , vol.41 , pp. 3706-3719
    • Ng, W.W.Y.1    Yeung, D.S.2    Firth, M.3    Tsang, E.C.C.4    Wang, X.-Z.5
  • 39
    • 82255192254 scopus 로고    scopus 로고
    • Comparative analysis of data mining methods for bankruptcy prediction
    • D.L. Olson, D. Delen, and Y. Meng Comparative analysis of data mining methods for bankruptcy prediction Decis. Supp. Syst. 52 2012 464 473
    • (2012) Decis. Supp. Syst. , vol.52 , pp. 464-473
    • Olson, D.L.1    Delen, D.2    Meng, Y.3
  • 40
    • 33646744577 scopus 로고    scopus 로고
    • Constructability practices to manage sustainable building knowledge
    • M.H. Pulaski, M.J. Horman, and D.R. Riley Constructability practices to manage sustainable building knowledge J. Archit. Eng. 12 2006 83 92
    • (2006) J. Archit. Eng. , vol.12 , pp. 83-92
    • Pulaski, M.H.1    Horman, M.J.2    Riley, D.R.3
  • 43
    • 78650330073 scopus 로고    scopus 로고
    • Greening project management practices for sustainable construction
    • L.B. Robichaud, and V.S. Anantatmula Greening project management practices for sustainable construction J. Manage. Eng. 27 2011 48 57
    • (2011) J. Manage. Eng. , vol.27 , pp. 48-57
    • Robichaud, L.B.1    Anantatmula, V.S.2
  • 44
    • 70649086974 scopus 로고    scopus 로고
    • Project feasibility study: The key to successful implementation of sustainable and socially responsible construction management practice
    • L.-Y. Shen, V.W.Y. Tam, L. Tam, and Y.-B. Ji Project feasibility study: the key to successful implementation of sustainable and socially responsible construction management practice J. Clean. Prod. 18 2010 254 259
    • (2010) J. Clean. Prod. , vol.18 , pp. 254-259
    • Shen, L.-Y.1    Tam, V.W.Y.2    Tam, L.3    Ji, Y.-B.4
  • 45
    • 65649138430 scopus 로고    scopus 로고
    • A systematic analysis of performance measures for classification tasks
    • M. Sokolova, and G. Lapalme A systematic analysis of performance measures for classification tasks Inf. Process. Manag. 45 2009 427 437
    • (2009) Inf. Process. Manag. , vol.45 , pp. 427-437
    • Sokolova, M.1    Lapalme, G.2
  • 46
    • 84863714416 scopus 로고    scopus 로고
    • Hybrid principal component analysis and support vector machine model for predicting the cost performance of commercial building projects using pre-project planning variables
    • H. Son, C. Kim, and C. Kim Hybrid principal component analysis and support vector machine model for predicting the cost performance of commercial building projects using pre-project planning variables Autom. Constr. 27 2012 60 66
    • (2012) Autom. Constr. , vol.27 , pp. 60-66
    • Son, H.1    Kim, C.2    Kim, C.3
  • 48
    • 84855913313 scopus 로고    scopus 로고
    • Project delivery metrics for sustainable, high-performance buildings
    • L. Swarup, S. Korkmaz, and D. Riley Project delivery metrics for sustainable, high-performance buildings J. Constr. Eng. Manage. 137 2011 1043 1051
    • (2011) J. Constr. Eng. Manage. , vol.137 , pp. 1043-1051
    • Swarup, L.1    Korkmaz, S.2    Riley, D.3
  • 49
    • 33748905735 scopus 로고    scopus 로고
    • U.s. Environmental Protection Agency EPA Web site
    • U.S. Environmental Protection Agency Basic Information 2010 EPA Web site http://www.epa.gov/greenbuilding/pubs/about.htm
    • (2010) Basic Information
  • 50
    • 78951482304 scopus 로고    scopus 로고
    • U.s. Environmental Protection Agency EPA Web site
    • U.S. Environmental Protection Agency Why Build Green? 2010 EPA Web site, http://www.epa.gov/greenbuilding/pubs/whybuild.htm
    • (2010) Why Build Green?
  • 53
    • 0002660750 scopus 로고    scopus 로고
    • The support vector method of function estimation
    • J.A.K. Suykens, J.P.L. Vandewalle, Springer New York, NY
    • V. Vapnik The support vector method of function estimation J.A.K. Suykens, J.P.L. Vandewalle, Nonlinear Modeling: Advanced Black Box Techniques 1998 Springer New York, NY 55 85
    • (1998) Nonlinear Modeling: Advanced Black Box Techniques , pp. 55-85
    • Vapnik, V.1
  • 55
    • 77949488890 scopus 로고    scopus 로고
    • A study of preproject planning and project success using ANNs and regression models
    • Y.-R. Wang, and G.E. Gibson A study of preproject planning and project success using ANNs and regression models Autom. Constr. 19 2010 341 346
    • (2010) Autom. Constr. , vol.19 , pp. 341-346
    • Wang, Y.-R.1    Gibson, G.E.2
  • 57
    • 84859217983 scopus 로고    scopus 로고
    • Predicting construction cost and schedule success using artificial neural networks ensemble and support vector machines classification models
    • Y.-R. Wang, C.-Y. Yu, and H.-H. Chan Predicting construction cost and schedule success using artificial neural networks ensemble and support vector machines classification models Int. J. Proj. Manage. 30 2012 470 478
    • (2012) Int. J. Proj. Manage. , vol.30 , pp. 470-478
    • Wang, Y.-R.1    Yu, C.-Y.2    Chan, H.-H.3
  • 58
    • 0034118581 scopus 로고    scopus 로고
    • Neural network credit scoring models
    • D. West Neural network credit scoring models Comput. Oper. Res. 27 2000 1131 1152
    • (2000) Comput. Oper. Res. , vol.27 , pp. 1131-1152
    • West, D.1
  • 60
    • 42949153286 scopus 로고    scopus 로고
    • Model of customer churn prediction on support vector machine
    • G.-E. Xia, and W.-D. Jin Model of customer churn prediction on support vector machine Syst. Eng. Theory Pract. 28 2008 71 77
    • (2008) Syst. Eng. Theory Pract. , vol.28 , pp. 71-77
    • Xia, G.-E.1    Jin, W.-D.2
  • 61
    • 84892449637 scopus 로고    scopus 로고
    • Paradigm shift toward sustainable commercial project development
    • X. Zhang Paradigm shift toward sustainable commercial project development Habitat Int. 42 2014 186 192
    • (2014) Habitat Int. , vol.42 , pp. 186-192
    • Zhang, X.1
  • 62
    • 79959949901 scopus 로고    scopus 로고
    • Green property development practice in China: Costs and barriers
    • X. Zhang, A. Platten, and L. Shen Green property development practice in China: costs and barriers Build. Environ. 46 2011 2153 2160
    • (2011) Build. Environ. , vol.46 , pp. 2153-2160
    • Zhang, X.1    Platten, A.2    Shen, L.3
  • 63
    • 78649326769 scopus 로고    scopus 로고
    • Green strategy for gaining competitive advantage in housing development: A China study
    • X. Zhang, L. Shen, and Y. Wu Green strategy for gaining competitive advantage in housing development: a China study J. Clean. Prod. 19 2011 157 167
    • (2011) J. Clean. Prod. , vol.19 , pp. 157-167
    • Zhang, X.1    Shen, L.2    Wu, Y.3
  • 64
    • 84867594311 scopus 로고    scopus 로고
    • Life cycle assessment of the air emissions during building construction process: A case study in Hong Kong, Renew
    • X. Zhang, L. Shen, and L. Zhang Life cycle assessment of the air emissions during building construction process: a case study in Hong Kong, Renew Sust. Energ. Rev. 17 2013 160 169
    • (2013) Sust. Energ. Rev. , vol.17 , pp. 160-169
    • Zhang, X.1    Shen, L.2    Zhang, L.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.