Surrogate model ( Active Learning) A surrogate model is an engineering method used when an outcome of interest cannot be easily directly measured, so a model of the outcome is used instead. Most engineering design problems require experiments and/or simulations to evaluate design objective and constraint functions as function of design variables. In surrogate model based optimization an initial surrogate is constructed using some of the available budget of expensive experiments and/or simulations. The remaining experiments/simulations are run for designs which the surrogate model predicts may have promising performance. The process usually takes the form of the following search/update procedure. 1. Initial sample selection (the experiments and/or simulations to be run) 2. Construct surrogate model 3. Search surrogate model (the model can be searched extensively, e.g. using a genetic algorithm, as it is cheap to evaluate) 4. Run and update experiment/simulation at new location(s) found by search and add to sample 5. Iterate steps until out of time or design good enough en.wikipedia.org/wiki/Surrogate_model
Posted on: Sun, 07 Dec 2014 07:51:26 +0000
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