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Volumn 1, Issue , 2009, Pages 521-525

Intelligent modeling and predicting surface roughness in end milling

Author keywords

[No Author keywords available]

Indexed keywords

BACK-PROPAGATION NEURAL NETWORKS; CUTTING PARAMETERS; DEPTH OF CUT; END MILLING; FEED-RATES; INPUT VECTOR; INTELLIGENT MODELING; MANUFACTURING CONDITIONS; MILLING CONDITIONS; PREDICTION MODEL; SPINDLE SPEED; SUPPORT VECTOR REGRESSIONS; TESTING DATA; TRAINING AND TESTING; TRAINING DATA SETS; TRAINING SPEED; WORK PIECES;

EID: 77950592886     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNC.2009.466     Document Type: Conference Paper
Times cited : (8)

References (10)
  • 1
    • 0037698093 scopus 로고    scopus 로고
    • Investigation of surface integrity in high speed end milling of a low alloyed steel
    • P. Chevrier, A. Tidu, B. Bolle, et al, "Investigation of surface integrity in high speed end milling of a low alloyed steel", International Journal of Machine Tools and Manufacture, 2003, vol.43, no.11, pp. 1135-1142.
    • (2003) International Journal of Machine Tools and Manufacture , vol.43 , Issue.11 , pp. 1135-1142
    • Chevrier, P.1    Tidu, A.2    Bolle, B.3
  • 2
    • 0037015550 scopus 로고    scopus 로고
    • Surface integrity of hot work tool steel after high speed milling-experimental data and empirical models
    • D. A. Axinte, R.C. Dewes, "Surface integrity of hot work tool steel after high speed milling-experimental data and empirical models", Journal of Materials Processing Technology, 2002, vol.127, no.3, pp. 325-335.
    • (2002) Journal of Materials Processing Technology , vol.127 , Issue.3 , pp. 325-335
    • Axinte, D.A.1    Dewes, R.C.2
  • 4
    • 0034817049 scopus 로고    scopus 로고
    • An integrated model of a fixtureworkpiece system for surface quality prediction
    • Y.G. Liao, S.J. Hu, "An integrated model of a fixtureworkpiece system for surface quality prediction", International Journal of Advanced Manufacturing Technology, 2001, vol.17, no.11, pp. 810-818.
    • (2001) International Journal of Advanced Manufacturing Technology , vol.17 , Issue.11 , pp. 810-818
    • Liao, Y.G.1    Hu, S.J.2
  • 5
    • 37149016011 scopus 로고    scopus 로고
    • Application of multiple regression and adaptive neuro fuzzy inference system for the prediction of surface roughness
    • S. Kumanan, C.P. Jesuthanam, R. Ashok Kumar, "Application of multiple regression and adaptive neuro fuzzy inference system for the prediction of surface roughness", International Journal of Advanced Manufacturing Technology, 2008, vol.35, no.7-8, pp. 778-788.
    • (2008) International Journal of Advanced Manufacturing Technology , vol.35 , Issue.7-8 , pp. 778-788
    • Kumanan, S.1    Jesuthanam, C.P.2    Kumar, R.A.3
  • 8
    • 33750343161 scopus 로고    scopus 로고
    • Milling surface roughness prediction using evolutionary programming methods
    • O. Colak, C. Kurbanoglu, M.C. Kayacan, "Milling surface roughness prediction using evolutionary programming methods", Materials and Design, 2007, vol.28, no.2, pp. 657-666.
    • (2007) Materials and Design , vol.28 , Issue.2 , pp. 657-666
    • Colak, O.1    Kurbanoglu, C.2    Kayacan, M.C.3
  • 10
    • 0043156348 scopus 로고    scopus 로고
    • Integrated genetic programming and genetic algorithm approach to predict surface roughness
    • M. Brezocnik, M. Kovacic, "Integrated genetic programming and genetic algorithm approach to predict surface roughness", Materials and Manufacturing Processes, 2003, vol.18, no.3, pp. 475-491.
    • (2003) Materials and Manufacturing Processes , vol.18 , Issue.3 , pp. 475-491
    • Brezocnik, M.1    Kovacic, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.