Some of the applications of neural network techniques in different methods, in computational electromagnetics, are highlighted. Applications in finite element method for automated mesh generation are described. Extrapolation of the FDTD data using FIR filterbased neural network is illustrated. Use o
Computational methods in optimization considering uncertainties – An overview
✍ Scribed by G.I. Schuëller; H.A. Jensen
- Publisher
- Elsevier Science
- Year
- 2008
- Tongue
- English
- Weight
- 241 KB
- Volume
- 198
- Category
- Article
- ISSN
- 0045-7825
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✦ Synopsis
This article presents a brief survey on some of the most relevant developments in the field of optimization under uncertainty. In particular, the scope and the relevance of the papers included in this Special Issue are analyzed. The importance of uncertainty quantification and optimization techniques for producing improved models and designs is thoroughly discussed. The focus of the discussion is in three specific research areas, namely reliability-based optimization, robust design optimization and model updating. The arguments presented indicate that optimization under uncertainty should become customary in engineering design in the foreseeable future. Computational aspects play a key role in analyzing and modeling realistic systems and structures.
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