Abstract
Global approximation for a complex “black-box” model (like a simulation model) with large domain or multi-dimensions can be applied in many fields such as parameter experiment, sensibility analysis, real-time simulation, and design/control optimization. For multi-dimensional global approximation, MARS (multi-variant adaptive regression splines) has unquestionable predominance over other common-used metamodel techniques. However, MARS has its own inevitable drawbacks which limit the range of its applications. This paper proposes a multi-dimensional global approximation method based improved MARS .Some tests and applications are given to prove the performance of the method.
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