Neural networks, grid computing, parallelization, high-dimensional optimization, quantitative investment, decision support. - Neuronale Netze, Parallelisierung, hoch-dimensionale Optimierung, quantitatives Investment, Entscheidungsunterstützung

In Unternehmen hat sich der Einsatz von rechenintensiver Informationstechnologie (IT) bereits für den Geschäftsbetrieb als unverzichtbar erwiesen, um Geschäftsprozesse besser auszurichten und neue Geschäftslösungen mit größerer Flexibilität und Geschwindigkeit bereitzustellen. Dieser...

Risk management has evolved as one of the key success factors for enterprises especially in the financial services industry. Itis highly demanding in terms of business requirements and technical resources, making it an almost ideal application fordistributed computing concepts like e.g. grid...

Risk/return management has not only evolved as one of the key success factors for enterprisesespecially in the financial services industry, but is in the times of the financial crisis crucial for thesurvival of a company. It demands powerful and at the same time flexible computational...

Grid Computing is a paradigmatic application forthe requirements associated with the exponentially growingcomplexity in the engineering, operation and maintenance oftoday’s information systems. Grid Computing comprises evergrowingglobal communication infrastructures and millions ofpossible...

The pressure on companies to respond flexibly to market changes has increased significantlyover the last years. This external pressure also affects in-house infrastructuresof information technology (IT) (Bieberstein et al. 2006, p. 1). Divisions and departmentswithin a company therefore need...

Any major research institution has a substantial number of computer systems on its campus, often in the scale of tens of thousands. Given that a large amount of scientific computing is appropriate for execution in an opportunistic environment, a campus grid is an inexpensive way to build a...

The PERFORMS self-assessment scheme measures individuals skills in identifying key mammographic features on setsof known cases. One aspect of this is that it allows radiologists’ skills to be trained, based on their data from this scheme.Consequently, a new strategy is introduced to provide...