Sensitivity Analysis of Laser Cutting Based on Metamodeling Approach
暂无分享,去创建一个
[1] Thomas J. Santner,et al. The Design and Analysis of Computer Experiments , 2003, Springer Series in Statistics.
[2] J. S. Hunter,et al. Statistics for experimenters : an introduction to design, data analysis, and model building , 1979 .
[3] Pijush Samui,et al. Handbook of Research on Advanced Computational Techniques for Simulation-Based Engineering , 2015 .
[4] Valerio Pascucci,et al. Visual Exploration of High Dimensional Scalar Functions , 2010, IEEE Transactions on Visualization and Computer Graphics.
[5] Padhraic Smyth,et al. From Data Mining to Knowledge Discovery in Databases , 1996, AI Mag..
[6] R. Bellman. Dynamic programming. , 1957, Science.
[7] Markus Nießen,et al. Optimization of partial differential equations for minimizing the roughness of laser cutting surfaces , 2010 .
[8] Daniel Asimov,et al. The grand tour: a tool for viewing multidimensional data , 1985 .
[9] Søren Nymand Lophaven,et al. DACE - A Matlab Kriging Toolbox, Version 2.0 , 2002 .
[10] Urs Eppelt,et al. Simulation of Laser Cutting , 2009 .
[11] Lars Mönch,et al. Simulation-based benchmarking of production control schemes for complex manufacturing systems , 2004 .
[12] Davide Ferrari,et al. Response improvement in complex experiments by co-information composite likelihood optimization , 2013, Statistics and Computing.
[13] Wolfgang Schulz,et al. A free boundary problem related to laser beam fusion cutting: ODE approximation , 1997 .
[14] Donald R. Jones,et al. Efficient Global Optimization of Expensive Black-Box Functions , 1998, J. Glob. Optim..
[15] M. Mongillo. Choosing Basis Functions and Shape Parameters for Radial Basis Function Methods , 2011 .
[16] Vinod Yadava,et al. Laser beam machining—A review , 2008 .
[17] Torsten Hermanns,et al. Analysis and optimal control for free melt flow boundaries in laser cutting with distributed radiation , 2015 .
[18] Rudolf Reinhard,et al. How Virtual Production Intelligence Can Improve Laser-Cutting Planning Processes , 2016 .
[19] Rudolf Reinhard,et al. The Contribution of Virtual Production Intelligence to Laser Cutting Planning Processes , 2014 .
[20] Wei Liu,et al. Social and physical interactive paradigms for mixed-reality entertainment , 2006, CIE.
[21] R. L. Hardy. Multiquadric equations of topography and other irregular surfaces , 1971 .
[22] Geoffrey M. Laslett,et al. Kriging and Splines: An Empirical Comparison of their Predictive Performance in Some Applications , 1994 .
[23] Max D. Morris,et al. Factorial sampling plans for preliminary computational experiments , 1991 .
[24] Florian Pappenberger,et al. Multi‐method global sensitivity analysis (MMGSA) for modelling floodplain hydrological processes , 2008 .
[25] Andreas Otto,et al. Numerical Simulations - A Versatile Approach for Better Understanding Dynamics in Laser Material Processing , 2011 .
[26] Juhani Heilala,et al. Decision Support Using Simulation for Customer-Driven Manufacturing System Design and Operations Planning , 2010 .
[27] R. L. Hardy. Theory and applications of the multiquadric-biharmonic method : 20 years of discovery 1968-1988 , 1990 .
[28] Jack P. C. Kleijnen,et al. State-of-the-Art Review: A User's Guide to the Brave New World of Designing Simulation Experiments , 2005, INFORMS J. Comput..
[29] C. Micchelli. Interpolation of scattered data: Distance matrices and conditionally positive definite functions , 1986 .
[30] Saltelli Andrea,et al. Global Sensitivity Analysis: The Primer , 2008 .
[31] R. Franke. Smooth Interpolation of Scattered Data by Local Thin Plate Splines , 1982 .
[32] A. Saltelli,et al. On the Relative Importance of Input Factors in Mathematical Models , 2002 .
[33] Bruce H. Thomas,et al. Emerging technologies of augmented reality - interfaces and design , 2006 .
[34] Shmuel Rippa,et al. An algorithm for selecting a good value for the parameter c in radial basis function interpolation , 1999, Adv. Comput. Math..
[35] Günther Schuh,et al. Technology roadmapping for the production in high-wage countries , 2011, Prod. Eng..