| | SLO | ENG | Cookies and privacy

Bigger font | Smaller font

Search the digital library catalog Help

Query: search in
search in
search in
search in
* old and bologna study programme

Options:
  Reset


1 - 3 / 3
First pagePrevious page1Next pageLast page
1.
2.
RAZVOJ KONCEPTOV DINAMIČNEGA METAPROGRAMIRANJA V STATIČNO TIPIZIRANEM OBJEKTNO USMERJENEM PROGRAMSKEM JEZIKU
Sašo Greiner, 2009, dissertation

Abstract: V delu predstavljamo načrtovanje in implementacijo metaprogramskih konceptov čistega objektno usmerjenega programskega jezika. Jezik, ki je nadgradnja obstoječega jezika Z0, imenujemo Zero. Temeljna ideja jezika je združitev konceptov dinamičnega metaprogramiranja s statičnim oz. hibridnim sistemom tipov. Metaprogramski model jezika temelji na behavioralni in strukturalni refleksiji, ki omogočata spremembe obnašanja in strukture programov v času izvajanja. Metafunkcionalnost je realizirana v metarazredih, ki dopolnjujejo obstoječo razredno hierarhijo. Čisti objektni model je razširjen na metode, s čimer so omogočene anonimne metode in metode višjega reda. V okviru statičnega sistema tipov vpeljemo metodne tipe, ki omogočajo tipiziranje metod v času prevajanja in ohranjanje varnosti tipov v času izvajanja.
Keywords: programski jeziki, behavioralna refleksija, strukturalna refleksija, metaprogramiranje, statično tipiziranje
Published: 07.04.2009; Views: 1944; Downloads: 128
.pdf Full text (796,42 KB)

3.
Performance comparison of self-adaptive and adaptive differential evolution algorithms
Janez Brest, Borko Bošković, Sašo Greiner, Viljem Žumer, Mirjam Sepesy Maučec, 2007, original scientific article

Abstract: Differential evolution (DE) has been shown to be a simple, yet powerful, evolutionary algorithm for global optimization. for many real problems. Adaptation, especially self-adaptation, has been found to be highly beneficial for adjusting control parameters, especially when done without any user interaction. This paper presents differential evolution algorithms, whichuse different adaptive or self-adaptive mechanisms applied to the control parameters. Detailed performance comparisons of these algorithms on the benchmark functions are outlined.
Keywords: differential evolution, control parameter, fitness function, optimization, self-adaption
Published: 01.06.2012; Views: 1257; Downloads: 55
URL Link to full text

Search done in 0.06 sec.
Back to top
Logos of partners University of Maribor University of Ljubljana University of Primorska University of Nova Gorica