2006
Finding Optimal Solutions of Energetic Remedial Equations with Genetic Algorithms
PAVLOVIČ, Jan a Jiří HŘEBÍČEKZákladní údaje
Originální název
Finding Optimal Solutions of Energetic Remedial Equations with Genetic Algorithms
Název česky
Nalezení optimálního řešení energetické rovnice pomocí genetických algoritmů
Autoři
PAVLOVIČ, Jan (203 Česká republika) a Jiří HŘEBÍČEK (203 Česká republika, garant)
Vydání
Austria, 20th International Conference on Informatics for Environmental Protection. Managing Environmental Knowledge, od s. 401-404, 4 s. 2006
Nakladatel
Shaker Verlag
Další údaje
Jazyk
angličtina
Typ výsledku
Stať ve sborníku
Obor
10201 Computer sciences, information science, bioinformatics
Stát vydavatele
Rakousko
Utajení
není předmětem státního či obchodního tajemství
Kód RIV
RIV/00216224:14110/06:00021681
Organizační jednotka
Lékařská fakulta
ISBN
3-8322-5321-1
Klíčová slova anglicky
Genetic Algorithms; Optimization; Energy Management
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 16. 7. 2008 20:14, prof. RNDr. Jiří Hřebíček, CSc.
V originále
This paper presents a new way of finding the optimal solution of energetic remedial process. These solutions came as a result of optimization of energetic equations. The new artificial computation engine based on genetic algorithms which are commonly used for optimization in general has proved suitable for this problem domain as well. However, we developed the solutions describing energetic equations from the other point of view. They show the hidden characteristics which are not always easy to specify. Genetic algorithms often demand huge amount of computer time. We had to design the specific type of the distributed service oriented solution to meet the demands of computing and integration to the existing software environment.
Česky
This paper presents a new way of finding the optimal solution of energetic remedial process. These solutions came as a result of optimization of energetic equations. The new artificial computation engine based on genetic algorithms which are commonly used for optimization in general has proved suitable for this problem domain as well. However, we developed the solutions describing energetic equations from the other point of view. They show the hidden characteristics which are not always easy to specify. Genetic algorithms often demand huge amount of computer time. We had to design the specific type of the distributed service oriented solution to meet the demands of computing and integration to the existing software environment.
Návaznosti
| MSM0021622412, záměr |
|