Scientists and engineers use computer simulations to study relationships between a model's input parameters and its outputs. However, thorough parameter studies are challenging, if not impossible, when the simulation is expensive and the model has several inputs. To enable studies in these instances, the engineer may attempt to reduce the dimension of the model's input parameter space. Active subspaces are an emerging set of dimension reduction tools that identify important directions in the parameter space. This book describes techniques for discovering a model's active subspace and proposes methods for exploiting the reduced dimension to enable otherwise infeasible parameter studies. Readers will find new ideas for dimension reduction, easy-to-implement algorithms, and several examples of active subspaces in action.1 2 3 4 5 6 10a13 10a12 10 a11 10 a10 10a9 10 a8 Index Ei g e n v a l u e s Grad Local Linear 1 2 3 4 5 6 10a13 10a12 10 a11 10 a10 10a9 10 ... More details of this specific test problem are given in section 3.4.2. ... The computing platform is MATLAB 2014a on a MacBook Air with a dual-core processor and 8 GB of RAM.
|Author||:||Paul G. Constantine|
|Publisher||:||SIAM - 2015-03-17|