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Volumn 33, Issue 11-12, 2007, Pages 1077-1086

Robust parameter design for signal-response systems by soft computing

Author keywords

Backpropagation network; Dynamic SN ratio; Response function modeling; Signal response systems; Simulated annealing

Indexed keywords

BACKPROPAGATION; FUNCTION EVALUATION; NEURAL NETWORKS; PARAMETER ESTIMATION; ROBUST CONTROL; SOFT COMPUTING;

EID: 34547778930     PISSN: 02683768     EISSN: 14333015     Source Type: Journal    
DOI: 10.1007/s00170-006-0551-1     Document Type: Article
Times cited : (7)

References (27)
  • 4
    • 0001426048 scopus 로고    scopus 로고
    • Parameter design for signal-response systems: A different look at Taguchi's dynamic parameter design
    • 2
    • Miller A, Wu CFJ (1996) Parameter design for signal-response systems: a different look at Taguchi's dynamic parameter design. Stat Sci 11(2):122-136
    • (1996) Stat Sci , vol.11 , pp. 122-136
    • Miller, A.1    Wu, C.F.J.2
  • 5
    • 0001894402 scopus 로고
    • Computer experiments for quality control by parameter design
    • Welch WJ, Yu TK, Kang SM, Sacks J (1990) Computer experiments for quality control by parameter design. J Qual Technol 22:15-22
    • (1990) J Qual Technol , vol.22 , pp. 15-22
    • Welch, W.J.1    Yu, T.K.2    Kang, S.M.3    Sacks, J.4
  • 6
    • 84952135282 scopus 로고
    • Economical experimentation method for robust design
    • Shoemaker AC, Tsui KL, Wu CFJ (1991) Economical experimentation method for robust design. Technometrics 33:415-427
    • (1991) Technometrics , vol.33 , pp. 415-427
    • Shoemaker, A.C.1    Tsui, K.L.2    Wu, C.F.J.3
  • 7
    • 0034588714 scopus 로고    scopus 로고
    • Optimization of parameter design: An intelligent approach using neural network and simulated annealing
    • 12
    • Su CT, Chang HH (2000) Optimization of parameter design: an intelligent approach using neural network and simulated annealing. Int J Syst Sci 31(12):1543-1549
    • (2000) Int J Syst Sci , vol.31 , pp. 1543-1549
    • Su, C.T.1    Chang, H.H.2
  • 8
    • 0030107298 scopus 로고    scopus 로고
    • Parameter design with dynamic characteristics: A regression perspective
    • Wasserman GS (1996) Parameter design with dynamic characteristics: a regression perspective. Qual Reliabil Eng Int 12:113-117
    • (1996) Qual Reliabil Eng Int , vol.12 , pp. 113117
    • Wasserman, G.S.1
  • 9
    • 0031187029 scopus 로고    scopus 로고
    • Graphical methods for robust design with dynamic characteristics
    • Lunani M, Nair VN, Wasserman GS (1997) Graphical methods for robust design with dynamic characteristics. J Qual Technol 29:327-338
    • (1997) J Qual Technol , vol.29 , pp. 327-338
    • Lunani, M.1    Nair, V.N.2    Wasserman, G.S.3
  • 10
    • 0031161876 scopus 로고    scopus 로고
    • Analysis dynamic robust design experiments
    • 6
    • McCaskey SD, Tsui KL (1997) Analysis dynamic robust design experiments. Int J Prod Res 35(6):1561-1574
    • (1997) Int J Prod Res , vol.35 , pp. 1561-1574
    • McCaskey, S.D.1    Tsui, K.L.2
  • 11
    • 0033328471 scopus 로고    scopus 로고
    • Modeling and analysis of dynamic robust design experiments
    • Tsui KL (1999) Modeling and analysis of dynamic robust design experiments. IIE Trans 31:1113-1122
    • (1999) IIE Trans , vol.31 , pp. 1113-1122
    • Tsui, K.L.1
  • 12
    • 0013291388 scopus 로고    scopus 로고
    • Analysis of parameter design experiments for signal-response systems
    • 2
    • Miller A (2002) Analysis of parameter design experiments for signal-response systems. J Qual Technol 34(2):139-151
    • (2002) J Qual Technol , vol.34 , pp. 139-151
    • Miller, A.1
  • 13
    • 1642560797 scopus 로고    scopus 로고
    • GLMs for the analysis of robust design with dynamic characteristics
    • 3
    • Lesperance ML, Park SM (2003) GLMs for the analysis of robust design with dynamic characteristics. J Qual Technol 35(3):253-263
    • (2003) J Qual Technol , vol.35 , pp. 253-263
    • Lesperance, M.L.1    Park, S.M.2
  • 14
    • 1342263565 scopus 로고    scopus 로고
    • Development of performance measures for dynamic parameter design problems
    • 1/2
    • Park YG, Yum BJ (2003) Development of performance measures for dynamic parameter design problems. Int J Manuf Technol Manage 5(1/2):91-104
    • (2003) Int J Manuf Technol Manage , vol.5 , pp. 91-104
    • Park, Y.G.1    Yum, B.J.2
  • 18
    • 0025449198 scopus 로고
    • Simulated annealing: A tool for operational research
    • Eglese RW (1990) Simulated annealing: a tool for operational research. Eur J Oper Res 46:271-281
    • (1990) Eur J Oper Res , vol.46 , pp. 271-281
    • Eglese, R.W.1
  • 19
    • 26444479778 scopus 로고
    • Optimization by simulated annealing
    • Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Sci 220:671-680
    • (1983) Sci , vol.220 , pp. 671-680
    • Kirkpatrick, S.1    Gelatt, C.D.2    Vecchi, M.P.3
  • 20
    • 0025903204 scopus 로고
    • A note on the effect of neighborhood structure in simulated annealing
    • 6
    • Cheh KM, Goldberg JB, Askin RG (1991) A note on the effect of neighborhood structure in simulated annealing. Comput Oper Res 18(6):537-547
    • (1991) Comput Oper Res , vol.18 , pp. 537-547
    • Cheh, K.M.1    Goldberg, J.B.2    Askin, R.G.3
  • 22
    • 0001967793 scopus 로고    scopus 로고
    • Using artificial neural networks for experimental design in off-line quality
    • Rowlands H, Packianather MS, Oztemel E (1996) Using artificial neural networks for experimental design in off-line quality. J Syst Eng 6:46-59
    • (1996) J Syst Eng , vol.6 , pp. 46-59
    • Rowlands, H.1    Packianather, M.S.2    Oztemel, E.3
  • 23
    • 0031199110 scopus 로고    scopus 로고
    • Response surface methodology: A neural network approach
    • Anjum MF, Tasaddug I, Ahaled AS (1997) Response surface methodology: a neural network approach. Eur J Oper Res 101:65-73
    • (1997) Eur J Oper Res , vol.101 , pp. 65-73
    • Anjum, M.F.1    Tasaddug, I.2    Ahaled, A.S.3
  • 24
    • 0032650376 scopus 로고    scopus 로고
    • Modeling, optimization and classification of weld quality in tungsten insert gas welding
    • Tarng YS, Tsai HL, Yeh SS (1999) Modeling, optimization and classification of weld quality in tungsten insert gas welding. Int J Mach Tool Manuf 39:1427-1438
    • (1999) Int J Mach Tool Manuf , vol.39 , pp. 1427-1438
    • Tarng, Y.S.1    Tsai, H.L.2    Yeh, S.S.3
  • 25
    • 0034246501 scopus 로고    scopus 로고
    • A hybrid neural network and simulated annealing approach to the unit commitment problem
    • Nayak R, Sharma JD (2000) A hybrid neural network and simulated annealing approach to the unit commitment problem. Comput Electron Eng 26:461-477
    • (2000) Comput Electron Eng , vol.26 , pp. 461-477
    • Nayak, R.1    Sharma, J.D.2
  • 26
    • 0037962054 scopus 로고    scopus 로고
    • ANNSA: A hybrid artificial neural network/simulated annealing algorithm for optimal control problem
    • Sarkar D, Modak JM (2003) ANNSA: a hybrid artificial neural network/simulated annealing algorithm for optimal control problem. Chem Eng Sci 58:3131-3142
    • (2003) Chem Eng Sci , vol.58 , pp. 3131-3142
    • Sarkar, D.1    Modak, J.M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.