PARAMETRIC SELECTION OF INDUSTRIAL ROBOTS USING REDUCED PCR/PLSR MODELS FOR BETTER ESTIMATES OF EXPECTED COST AND SPECIFICATIONS
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References
. R.P. Paul, and Shimon Y. Nof, “Work Methods Measurement: A Comparison Between Robot and Human Task Performanceâ€,Taylor&Francis,IFPR, Volume:17, Issue:3, Pages:277-303, 1979.
. V.P. Agrawal and V.Kohli, S. Gupta, “Computer-Aided Robot Selection: the Multiple-Attribute Decision Making an Approachâ€,International Journal of Production Research, Volume:29, Issue:8, Pages: 1629-1644, 1991.
. ÅženimÖzgürler, Ali F. Güneri,BahadırGülsün, OnurYılmaz,“Robot Selection for a Flexible Manufacturing System with AHP and TOPSISMethodâ€, 15th International Research Conference on TMT-2011, Prague, Czech-Republic, 2011.
. M.Z. Rehman, N.M. Nawi, “The Effect of Adaptive Momentum in Improving Accuracy of Gradient Descent Backpropagation Algorithm on Classification Problemsâ€, Springer-Verlag, Volume:179, Pages: 380-390, 2011.
. G.H. Liang, and M.J. Wang, “A Fuzzy Multicriteria Decision-Making Approach for Robot Selectionâ€,Robotics, and Computer-Aided Manufacturing, Volume:10, Pages: 267-274, 1993.
. M. Vukobratovic, “Scientific Fundamentals of Industrial Robots1: Dynamics of Manipulator Robots Theory and Applicationsâ€,Springer-Verlag Publication, New York, 1982.
. M. Khouja, “The Use of Data Envelopment Analysis for Technology Selectionâ€, Computer Industrial Eng., Volume:28, Pages: 123-132, 1995.
. T.C. Chu, and Y.C. Lin, “A Fuzzy-TOPSIS Method for Robot Selectionâ€,International Journal of Advanced Manufacturing Technology, Volume:21, Pages: 284-290, 2003.
. C. Parkan, M.L. Wu, “Decision-Making and Performance Measurement Models with Applications to Robot Selectionâ€,Computer Industrial. Eng., Volume:36, Issue:3, Pages: 503-523, 1999.
. R.V. Rao, K.K. Padmanabhan, “Selection, Identification and Comparison of Industrial Robots Using Digraph andMatrix Methodsâ€,Elsevier, Robotics, and Computer Integrated Manufacturing, Volume:22, Issue:4, Pages: 373-383, 2006.
. SuprakashMondal, S.Chakraborty, “A Solution to Robot Selection Problems Using Data Envelopment Analysisâ€, International Journal of Ind. Eng. Computations, Volume:4, Issue:3, Pages:355-372, 2013.
. Bouman, B. A. M., (1992). Linking physical remote sensing models with crop growth simulation models, applied for sugar beet. International Journal of Remote Sensing, 13, 2565–2581.
. Burgers, G., Van Leeuwen, P. J., &Evensen, G. (1998). Analysis scheme in the ensemble Kalman filter. Monthly Weather Bulletin, 126, 1719–1724.
. Nicole Kr¨amer, Masashi Sugiyama, The Degrees of Freedom of Partial Least Squares Regression, Journal of the American Statistical Association, Page: 1-23, 2011.
. B. Efron, The Estimation of Prediction Error: Covariance Penalties and Cross-Validation. Journal of the American Statistical Association, 99(467):619–633, 2004.
. I. Frank, and J. Friedman, A Statistical View of Some Chemometrics Regression Tools. Technometrics, 35(2):109–135, 1993.
. Carsten Neumann, Michael Förster, Birgit Kleinschmit, Sibylle Itzerott, Utilizing a PLSR-Based Band-Selection Procedure for Spectral Feature Characterization of Floristic Gradients, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Volume: 9, Issue: 9, Pages:3982 - 3996, Sept. 2016.