Title :
Inductive learning for optimization of simulation model output
Author :
Barton, Rainer ; Szczerbicka, Helena
Author_Institution :
Inst. for Flight Mech., German Aerosp. Center, Braunschweig, Germany
Abstract :
In this article we present the optimization approach, `ML-Opt´, which approximates the structure of an unknown goal function by analyzing functional dependency between search points. The functional dependency is determined by an inductive learning algorithm, which generates a classifier used as a control structure in the optimization process. A numerical example and discussions are presented
Keywords :
learning by example; optimisation; simulation; ML-Opt; functional dependency analysis; goal function structure approximation; inductive learning algorithm; simulation model output optimization; Computational modeling; Computer science; Genetic algorithms; Machine learning; Machine learning algorithms; Mathematics; Optimization methods; Simulated annealing; Space exploration; Stochastic processes;
Conference_Titel :
Intelligent Processing and Manufacturing of Materials, 1999. IPMM '99. Proceedings of the Second International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-5489-3
DOI :
10.1109/IPMM.1999.792488
