213
Views
32
CrossRef citations to date
0
Altmetric
ORIGINAL ARTICLES

Selection and validation of predictive regression and neural network models based on designed experiments

, &
Pages 13-23 | Received 01 Oct 2002, Accepted 01 Mar 2005, Published online: 23 Feb 2007

References

  • Baum , E. B. and Haussler , D. 1989 . What net size gives valid generalization? . Neural Computation , 1 ( 1 ) : 151 – 160 . [CSA]
  • Boothroyd , G. and Knight , W. A. 1989 . Fundamentals of Machining and Machine Tools , New York, NY : Marcel Dekker .
  • Breiman , L. and Spector , P. 1992 . Submodel selection and evaluation in regression: the X-random case . International Statistics Review , 60 ( 3 ) : 291 – 319 . [CSA]
  • Burnham , K. P. and Anderson , D. R. 2002 . Model Selection and Inference: A Practical Information—Theoretic Approach, , 2nd edn. , New York, NY : Springer-Verlag .
  • Coit , D. W. , Jackson , B. T. and Smith , A. E. 1998 . Static neural network process models: considerations and case studies . International Journal of Production Research , 36 ( 11 ) : 2953 – 2967 . [CSA] [CROSSREF]
  • Draper , N. R. and Smith , H. 1998 . Applied Regression Analysis, , 3rd edn. , New York, NY : Wiley .
  • Efron , B. and Tibshirani , R. 1998 . An Introduction to the Bootstrap , Boca Raton, FL : Chapman & Hall/CRC .
  • Feng , C. -X. 2001 . “ Experimental study of the effect of turning parameters on surface roughness in finish turning ” . In Proceedings of the 2001 Industrial Engineering Research Conference , Norcross, GA : Institute of Industrial Engineers . paper 2036
  • Feng , C. -X. and Wang , X. -F. 2002a . Digitizing uncertainty modeling for reverse engineering applications: regression vs. neural networks . Journal of Intelligent Manufacturing , 13 ( 3 ) : 189 – 199 . [CSA] [CROSSREF]
  • Feng , C. -X. and Wang , X. -F. 2002b . Development of empirical models for surface roughness prediction in finish turning . International Journal of Advanced Manufacturing Technology , 20 ( 5 ) : 348 – 356 . [CSA] [CROSSREF]
  • Feng , C. -X. and Wang , X. -F. 2003 . Surface roughness predictive modeling: neural networks versus regression . IIE Transactions , 35 ( 1 ) : 11 – 27 . [CSA] [CROSSREF]
  • Feng , C. -X. , Wang , X. -F. and Yu , Z. 2002 . Neural networks modeling of honing surface roughness parameters defined by ISO13565 . SME Journal of Manufacturing Systems , 21 ( 5 ) : 398 – 408 . [CSA]
  • Feng , C. -X. and Yu , Z. 2003 . Neural networks modeling of turning surface roughness parameters defined by ISO13565 , Transactions of the NAMRI/SME 467 – 474 . Dearborn, MI : Society of Manufacturing Engineers . Technical Paper No. MS03-202
  • Feng , C. -X. , Yu , Z. and Wang , J. -H. 2004 . Validation and data splitting in predictive regression modeling of honing surface roughness data . International Journal of Production Research , 43 ( 8 ) : 1555 – 1571 . [CSA]
  • Gershenfeld , N. 1999 . The Nature of Mathematical Modeling , Cambridge, UK : Cambridge University Press .
  • Gilmour , S. -G. 1996 . The interpretation of Mallows C p -statistic . The Statistician , 45 ( 1 ) : 49 – 56 . [CSA]
  • Girossi , F. and Poggio , T. 1989 . Representation qualities of neural networks: Kolmogorov's theorem is irrelevant . Neural Computation , 1 ( 4 ) : 465 – 469 . [CSA]
  • Gorman , J. -W. and Torman , R. -J. 1966 . Selection of variables for fitting equations to data . Technometrics , 8 ( 1 ) : 27 – 51 . [CSA]
  • Groover , M. -P. 2002 . Fundamentals of Modern Manufacturing, , 2nd edn. , New York, NY : Wiley .
  • Groth , R. 1998 . Data Mining: A Hands on Approach for Business Professionals , Upper Saddle River, NJ : Prentice Hall .
  • Hastie , T. , Tibshirani , R. and Friedman , J. 2001 . The Elements of Statistical Learning: Data Mining, Inference, and Prediction , New York, NY : Springer .
  • Secht-Nelson , R. 1987 . “ Kolmogorov's mapping neural network existence theorem ” . In Proceedings of the 1st IEEE Annual International Conference on Neural Networks , III.11 – III.14 . Piscataway, NJ : IEEE Press .
  • Kalpakjian , S. and Schmid , S. R. 2003 . Manufacturing Processes for Engineering Materials, , 4th edn. , Upper Saddle River, NJ : Prentice Hall .
  • Kapse , P. 2001 . The effect of turning parameters on surface roughness in finish turning , MS Project Report Peoria, IL : Department of Industrial and Manufacturing Engineering, Bradley University .
  • Kolen , J. -F. and Pollack , J. B. 1990 . Backpropagation is sensitive to initial conditions . Complex Systems , 4 ( 3 ) : 269 – 280 . [CSA]
  • Kurkova , V. 1991 . Kolmogorov's theorem is relevant . Neural Computing , 3 ( 4 ) : 617 – 622 . [CSA]
  • Kusiak , A. 2000a . Computational Intelligence in Design and Manufacturing , New York, NY : Wiley .
  • Kusiak , A. 2000b . Decomposition in data mining: an industrial case study . IEEE Transactions on Electronics Packaging Manufacturing , 23 ( 4 ) : 345 – 353 . [CSA] [CROSSREF]
  • Kusiak , A. and Kurasek , C. 2001 . Data mining of printed circuit boards . IEEE Transactions on Robotics and Automation , 17 ( 2 ) : 191 – 196 . [CSA] [CROSSREF]
  • Lawrence , J. 1994 . Introduction to Neural Networks: Design, Theory, and Applications, , 6th edn. , Nevada City, CA : California Scientific Software .
  • Lawrence , J. and Fredrickson , J. 1998 . BrainMaker User's Guide and Reference Manual, , 7th edn. , Nevada City, CA : California Scientific Software .
  • Lippmann , R. P. An introduction to computing with neural nets . April 4–22 . IEEE Acoustics, Speech and Signal Processing Magazine ,
  • Mallows , C. L. 1973 . Some comments on C p . Technometrics , 15 ( 4 ) : 661 – 675 . [CSA]
  • Mallows , C. L. 1995 . More comments on C p . Technometrics , 37 ( 4 ) : 362 – 372 . [CSA]
  • Mallows , C. L. 1997 . C p and prediction with many regressors: comments on Mallows (1995) . Technometrics , 39 ( 1 ) : 115 – 116 . [CSA]
  • Marchandani , G. and Cao , W. 1989 . On hidden nodes for neural nets . IEEE Transactions on Circuits and Systems , 36 ( 5 ) : 661 – 664 . [CSA] [CROSSREF]
  • Miller , A. J. 2002 . Subset Selection in Regression, , 2nd edn. , Boca Raton, FL : Chapman & Hall .
  • Miller , R. -G. 1974 . The jackknife—a review . Biometrika , 61 ( 1 ) : 1 – 15 . [CSA]
  • Mitchell , T. -M. 1997 . Machine Learning , New York, NY : McGraw-Hill .
  • Montgomery , D. -C. , Peck , E. -A. and Vining , G. -G. 2001 . Introduction to Linear Regression Analysis, , 3rd edn. , New York, NY : Wiley .
  • Shaw , M. 1984 . Metal Cutting Principles , Oxford, UK : Oxford University Press .
  • Swingler , K. 1996 . Applying Neural Networks: A Practical Guide , San Francisco, CA : Morgan Kaufmann .
  • Thompson , M. -L. 1978a . Selection of variables in multiple regression: part I—a review and evaluation . International Statistical Review , 46 ( 1 ) : 1 – 19 . [CSA]
  • Thompson , M. -L. 1978b . Selection of variables in multiple regression: part II—chosen procedures, computations and examples . International Statistial Review , 46 ( 2 ) : 129 – 146 . [CSA]
  • Twomey , J. -M. and Smith , A. E. 1998 . Bias and variance of validation methods for function approximation neural networks under conditions of sparse data . IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), , 28 ( 3 ) : 417 – 430 . [CSA] [CROSSREF]
  • Wasserman , P. D. 1989 . Neural Computing: Theory and Practice , New York, NY : Van Nostrand Reinhold .
  • Witten , I. -H. and Frank , E. 2000 . Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations , San Francisco, CA : Morgan Kaufmann .
  • Zhang , P. 1993 . Model selection via multifold cross-validation . Annals of Statistics , 21 ( 1 ) : 299 – 311 . [CSA]
  • Yu , Z. -G. 2003 . Selection and validation of predictive regression and neural networks models for experimental data from machining surface roughness studies , MS thesis Peoria, IL : Department of Industrial and Manufacturing Engineering, Bradley University .

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.