메뉴 건너뛰기




Volumn 48, Issue 10, 2009, Pages 4899-4907

Genetic programming based variable interaction models for classification of process and biological systems

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION APPROACH; CLASSIFICATION OF DATA; COMPLEX NATURE; COMPLEX PROCESSES; DATA SETS; DATA-DRIVEN; DECISION BOUNDARY; FEATURE VECTORS; HIGHLY NONLINEAR; MODEL-BASED; MODELING APPROACH; MULTIPLE CLASS; NONLINEAR CLASSIFIERS; POTENTIAL TOOL; VARIABLE DEPENDENCIES; VARIABLE INTERACTION;

EID: 67249101970     PISSN: 08885885     EISSN: None     Source Type: Journal    
DOI: 10.1021/ie801147m     Document Type: Article
Times cited : (9)

References (31)
  • 5
    • 0032781888 scopus 로고    scopus 로고
    • Comparative study of class data analysis with PCALDA, SIMCA, PLS, ANNs, and k-NN
    • Tominaga, Y. Comparative study of class data analysis with PCALDA, SIMCA, PLS, ANNs, and k-NN. Chemom. Intell. Lab. Syst. 1999, 49, 105-115.
    • (1999) Chemom. Intell. Lab. Syst , vol.49 , pp. 105-115
    • Tominaga, Y.1
  • 6
    • 2342505830 scopus 로고    scopus 로고
    • Fault diagnosis based on Fisher discriminant analysis and support vector machines
    • Chiang, L. H.; Kotanchek, M. E.; Kordon, A. K. Fault diagnosis based on Fisher discriminant analysis and support vector machines. Comput. Chem. Eng. 2004, 28, 1389-1401.
    • (2004) Comput. Chem. Eng , vol.28 , pp. 1389-1401
    • Chiang, L.H.1    Kotanchek, M.E.2    Kordon, A.K.3
  • 7
    • 24044435942 scopus 로고    scopus 로고
    • Reducing multiclass to binary: A unifying approach for margin classifiers
    • Allwein, E. L.; Schapire, R. E.; Singer, Y. Reducing multiclass to binary: A unifying approach for margin classifiers. J. Mach. Learn. Res. 2000, 1, 113-141.
    • (2000) J. Mach. Learn. Res , vol.1 , pp. 113-141
    • Allwein, E.L.1    Schapire, R.E.2    Singer, Y.3
  • 8
    • 0025458937 scopus 로고
    • Process fault detection and diagnosis using neural networks-I. Steady-state processes
    • Venkatasubramanian, V.; Vaidyanathan, R.; Yamamoto, Y. Process fault detection and diagnosis using neural networks-I. Steady-state processes. Comput. Chem. Eng. 1990, 14 (7), 699-712.
    • (1990) Comput. Chem. Eng , vol.14 , Issue.7 , pp. 699-712
    • Venkatasubramanian, V.1    Vaidyanathan, R.2    Yamamoto, Y.3
  • 10
    • 2442612945 scopus 로고    scopus 로고
    • An ant colony classifier system: Application to some process engineering problems
    • Shelokar, P. S.; Jayaraman, V. K.; Kulkarni, B. D. An ant colony classifier system: application to some process engineering problems. Comput. Chem. Eng. 2004, 28, 1577-1584.
    • (2004) Comput. Chem. Eng , vol.28 , pp. 1577-1584
    • Shelokar, P.S.1    Jayaraman, V.K.2    Kulkarni, B.D.3
  • 11
    • 51649120537 scopus 로고    scopus 로고
    • Variable predictive modelssa new multivariate classification approach for pattern recognition applications
    • Rao, R.; Lakshminarayanan, S. Variable predictive modelssa new multivariate classification approach for pattern recognition applications. Pattern Recognit. 2009, 42 (1), 7-16.
    • (2009) Pattern Recognit , vol.42 , Issue.1 , pp. 7-16
    • Rao, R.1    Lakshminarayanan, S.2
  • 13
    • 33847147151 scopus 로고    scopus 로고
    • Variable interaction modeling approach for class discrimination in biological systems
    • Rao, R.; Lakshminarayanan, S. VPMCD: Variable interaction modeling approach for class discrimination in biological systems. FEBS Lett. 2007, 581, 826-830.
    • (2007) FEBS Lett , vol.581 , pp. 826-830
    • Rao, R.1    Lakshminarayanan2    VPMCD, S.3
  • 16
    • 19844362946 scopus 로고    scopus 로고
    • Genetic Programming for the Identification of Nonlinear Input-Output Models
    • Madar, J.; Abonyi, J.; Szeifert, F. Genetic Programming for the Identification of Nonlinear Input-Output Models. Ind. Eng. Chem. Res. 2005, 44 (9), 3178-3186.
    • (2005) Ind. Eng. Chem. Res , vol.44 , Issue.9 , pp. 3178-3186
    • Madar, J.1    Abonyi, J.2    Szeifert, F.3
  • 17
    • 0030195838 scopus 로고    scopus 로고
    • Nonlinear model structure identification using genetic programming and a block diagram oriented simulation tool
    • Gray, G. J.; Murray-Smith, D. J.; Li, Y.; Sharman, K. C. Nonlinear model structure identification using genetic programming and a block diagram oriented simulation tool. Electron. Lett. 1996, 32, 1422-1424.
    • (1996) Electron. Lett , vol.32 , pp. 1422-1424
    • Gray, G.J.1    Murray-Smith, D.J.2    Li, Y.3    Sharman, K.C.4
  • 19
    • 0242642746 scopus 로고    scopus 로고
    • Dynamic systems modelling using genetic programming
    • Hinchliffe, M. P.; Willis, M. J. Dynamic systems modelling using genetic programming. Comput. Chem. Eng. 2003, 27, 1841-1854.
    • (2003) Comput. Chem. Eng , vol.27 , pp. 1841-1854
    • Hinchliffe, M.P.1    Willis, M.J.2
  • 20
    • 9544238145 scopus 로고    scopus 로고
    • Adaptive genetic programming for steady-state process modeling
    • Grosman, B.; Lewin, D. R. Adaptive genetic programming for steady-state process modeling. Comput. Chem. Eng. 2004, 28 (12), 2779- 2790.
    • (2004) Comput. Chem. Eng , vol.28 , Issue.12 , pp. 2779-2790
    • Grosman, B.1    Lewin, D.R.2
  • 21
    • 0034266799 scopus 로고    scopus 로고
    • Application of Genetic Programming for Multicategory Pattern Classification
    • Kishore, J. K.; Patnaik, L. M.; Mani, V.; Agrawal, V. K. Application of Genetic Programming for Multicategory Pattern Classification. IEEE Trans. Evol. Comput. 2000, 4 (3), 242-258.
    • (2000) IEEE Trans. Evol. Comput , vol.4 , Issue.3 , pp. 242-258
    • Kishore, J.K.1    Patnaik, L.M.2    Mani, V.3    Agrawal, V.K.4
  • 22
    • 2442688288 scopus 로고    scopus 로고
    • Genetic programming in classifying large-scale data: An ensemble method
    • Zhang, Y.; Bhattacharyya, S. Genetic programming in classifying large-scale data: an ensemble method. Inf. Sci. 2004, 163, 85-101.
    • (2004) Inf. Sci , vol.163 , pp. 85-101
    • Zhang, Y.1    Bhattacharyya, S.2
  • 23
    • 33845434311 scopus 로고    scopus 로고
    • Fault classification using genetic programming
    • Zhang, L.; Nandi, A. K. Fault classification using genetic programming. Mech. Syst. Signal Process. 2007, 21, 1273-1284.
    • (2007) Mech. Syst. Signal Process , vol.21 , pp. 1273-1284
    • Zhang, L.1    Nandi, A.K.2
  • 26
    • 1542268315 scopus 로고    scopus 로고
    • Multi-class cancer subtype classification based on gene expression signatures with reliability analysis
    • Fua, L. M.; Fu-Liu, C. S. Multi-class cancer subtype classification based on gene expression signatures with reliability analysis. FEBS Lett. 2004, 561, 186-190.
    • (2004) FEBS Lett , vol.561 , pp. 186-190
    • Fua, L.M.1    Fu-Liu, C.S.2
  • 27
    • 67249153001 scopus 로고    scopus 로고
    • Identification of algebraic and state space models using genetic programming
    • Presented at, Boston, MA, July 5-7
    • Tun, K.; Lakshminarayanan, S. Identification of algebraic and state space models using genetic programming. Presented at DYCOPS 2004, Boston, MA, July 5-7, 2004.
    • (2004) DYCOPS
    • Tun, K.1    Lakshminarayanan, S.2
  • 28
    • 67249085960 scopus 로고    scopus 로고
    • MATLAB 7.0.4, release 14; The MathWorks Inc, Natick, MA, 2005
    • MATLAB 7.0.4, release 14; The MathWorks Inc.: Natick, MA, 2005.
  • 29
    • 0021427712 scopus 로고
    • Principal variables
    • McCabe, G. P. Principal variables. Technometrics 1984, 26, 137- 144.
    • (1984) Technometrics , vol.26 , pp. 137-144
    • McCabe, G.P.1
  • 30
    • 33745561205 scopus 로고    scopus 로고
    • An introduction to variable and feature selection
    • Guyon, I.; Elisseeff, A. An introduction to variable and feature selection. J. Mach. Learn. Res. 2003, 3, 1157-1182.
    • (2003) J. Mach. Learn. Res , vol.3 , pp. 1157-1182
    • Guyon, I.1    Elisseeff, A.2
  • 31
    • 33847330193 scopus 로고    scopus 로고
    • Partial correlation based variable selection approach for multivariate data classification method
    • Rao, R. K.; Lakshminarayanan, S. Partial correlation based variable selection approach for multivariate data classification method. Chemom. Intell. Lab. Syst. 2007, 86 (1), 68-81.
    • (2007) Chemom. Intell. Lab. Syst , vol.86 , Issue.1 , pp. 68-81
    • Rao, R.K.1    Lakshminarayanan, S.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.