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| Content Provider | Springer Nature Link |
|---|---|
| Author | Gajda Zagórska, Ewa Schaefer, Robert Smołka, Maciej Paszyński, Maciej Pardo, David |
| Copyright Year | 2014 |
| Abstract | This paper focuses on the application of hp hierarchic genetic strategy (hp–HGS) for solution of a challenging problem, the inversion of 3D direct current (DC) resistivity logging measurements. The problem under consideration has been formulated as the global optimization one, for which the objective function (misfit between computed and reference data) exhibits multiple minima. In this paper, we consider the extension of the hp–HGS strategy, namely we couple the hp–HGS algorithm with a gradient based optimization method for a local search. Forward simulations are performed with a self-adaptive hp finite element method, hp–FEM. The computational cost of misfit evaluation by hp–FEM depends strongly on the assumed accuracy. This accuracy is adapted to the tree of populations generated by the hp–HGS algorithm, which makes the global phase significantly cheaper. Moreover, tree structure of demes as well as branch reduction and conditional sprouting mechanism reduces the number of expensive local searches up to the number of minima to be recognized. The common (direct and inverse) accuracy control, crucial for the hp–HGS efficiency, has been motivated by precise mathematical considerations. Numerical results demonstrate the suitability of the proposed method for the inversion of 3D DC resistivity logging measurements. |
| Starting Page | 355 |
| Ending Page | 374 |
| Page Count | 20 |
| File Format | |
| ISSN | 15677818 |
| Journal | Natural Computing |
| Volume Number | 14 |
| Issue Number | 3 |
| e-ISSN | 15729796 |
| Language | English |
| Publisher | Springer Netherlands |
| Publisher Date | 2014-07-24 |
| Publisher Place | Dordrecht |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Hierarchic genetic strategy Inverse problem Hybrid method Theory of Computation Evolutionary Biology Processor Architectures Artificial Intelligence (incl. Robotics) Statistical Physics, Dynamical Systems and Complexity |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Science Applications |
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