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Title: Computer Experiments for Function Approximations

Computer Experiments for Function Approximations This research project falls in the domain of response surface methodology, which seeks cost-effective ways to accurately fit an approximate function to experimental data. Modeling and computer simulation are essential tools in modern science and engineering. A computer simulation can be viewed as a function that receives input from a given parameter space and produces an output. Running the simulation repeatedly amounts to an equivalent number of function evaluations, and for complex models, such function evaluations can be very time-consuming. It is then of paramount importance to intelligently choose a relatively small set of sample points in the parameter space at which to evaluate the given function, and then use this information to construct a surrogate function that is close to the original function and takes little time to evaluate. This study was divided into two parts. The first part consisted of comparing four sampling methods and two function approximation methods in terms of efficiency and accuracy for simple test functions. The sampling methods used were Monte Carlo, Quasi-Random LP{sub {tau}}, Maximin Latin Hypercubes, and Orthogonal-Array-Based Latin Hypercubes. The function approximation methods utilized were Multivariate Adaptive Regression Splines (MARS) and Support Vector Machines (SVM). The second part of the study more » concerned adaptive sampling methods with a focus on creating useful sets of sample points specifically for monotonic functions, functions with a single minimum and functions with a bounded first derivative. « less
Authors: ; ; ; ; ;
Publication Date:
OSTI Identifier:923129
Report Number(s):UCRL-TR-235618
TRN: US200806%%374
DOE Contract Number:W-7405-ENG-48
Resource Type:Technical Report
Data Type:
Research Org:Lawrence Livermore National Laboratory (LLNL), Livermore, CA
Sponsoring Org:USDOE
Country of Publication:United States
Language:English
Subject: 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; ACCURACY; APPROXIMATIONS; COMPUTERIZED SIMULATION; COMPUTERS; EFFICIENCY; SAMPLING; SIMULATION; VECTORS