Refine
Year of publication
- 2015 (162) (remove)
Institute
- Fachbereich Medizintechnik und Technomathematik (59)
- INB - Institut für Nano- und Biotechnologien (35)
- IfB - Institut für Bioengineering (30)
- Fachbereich Luft- und Raumfahrttechnik (23)
- Fachbereich Chemie und Biotechnologie (22)
- Fachbereich Elektrotechnik und Informationstechnik (22)
- Fachbereich Maschinenbau und Mechatronik (13)
- Fachbereich Energietechnik (12)
- Fachbereich Bauingenieurwesen (9)
- MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik (6)
Has Fulltext
- no (162) (remove)
Language
- English (162) (remove)
Document Type
- Article (83)
- Conference Proceeding (57)
- Part of a Book (17)
- Doctoral Thesis (3)
- Patent (1)
- Report (1)
Keywords
- Attitude dynamics (1)
- Booster Station (1)
- Carsharing (1)
- Charging stations (1)
- Discrete Optimisation (1)
- Discrete Optimization (1)
- E-carsharing (1)
- E-mobility (1)
- Efficiency (1)
- Electrical vehicle (1)
Is part of the Bibliography
- no (162)
Data-driven prediction and prevention of extreme events in a spatially extended excitable system
(2015)
Let X₁,…,Xₙ be independent and identically distributed random variables with distribution F. Assuming that there are measurable functions f:R²→R and g:R²→R characterizing a family F of distributions on the Borel sets of R in the way that the random variables f(X₁,X₂),g(X₁,X₂) are independent, if and only if F∈F, we propose to treat the testing problem H:F∈F,K:F∉F by applying a consistent nonparametric independence test to the bivariate sample variables (f(Xᵢ,Xⱼ),g(Xᵢ,Xⱼ)),1⩽i,j⩽n,i≠j. A parametric bootstrap procedure needed to get critical values is shown to work. The consistency of the test is discussed. The power performance of the procedure is compared with that of the classical tests of Kolmogorov–Smirnov and Cramér–von Mises in the special cases where F is the family of gamma distributions or the family of inverse Gaussian distributions.
Cheap does not imply cost-effective -- this is rule number one of zeitgeisty system design. The initial investment accounts only for a small portion of the lifecycle costs of a technical system. In fluid systems, about ninety percent of the total costs are caused by other factors like power consumption and maintenance. With modern optimization methods, it is already possible to plan an optimal technical system considering multiple objectives. In this paper, we focus on an often neglected contribution to the lifecycle costs: downtime costs due to spontaneous failures. Consequently, availability becomes an issue.