Detailed Information on Publication Record

PAVLOVIČ, Jan and Jiří HŘEBÍČEK. Finding Optimal Solutions of Energetic Remedial Equations with Genetic Algorithms. In 20th International Conference on Informatics for Environmental Protection. Managing Environmental Knowledge. Austria: Shaker Verlag, 2006, p. 401-404. ISBN 3-8322-5321-1.

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Basic information
Original name	Finding Optimal Solutions of Energetic Remedial Equations with Genetic Algorithms
Name in Czech	Nalezení optimálního řešení energetické rovnice pomocí genetických algoritmů
Authors	PAVLOVIČ, Jan (203 Czech Republic) and Jiří HŘEBÍČEK (203 Czech Republic, guarantor).
Edition	Austria, 20th International Conference on Informatics for Environmental Protection. Managing Environmental Knowledge, p. 401-404, 4 pp. 2006.
Publisher	Shaker Verlag

Other information
Original language	English
Type of outcome	Proceedings paper
Field of Study	10201 Computer sciences, information science, bioinformatics
Country of publisher	Austria
Confidentiality degree	is not subject to a state or trade secret
RIV identification code	RIV/00216224:14110/06:00021681
Organization unit	Faculty of Medicine
ISBN	3-8322-5321-1
Keywords in English	Genetic Algorithms; Optimization; Energy Management
Tags	Energy Management, Genetic algorithms, Optimization
Tags	International impact, Reviewed
Changed by	Changed by: prof. RNDr. Jiří Hřebíček, CSc., učo 993. Changed: 16/7/2008 20:14.

Abstract
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.

Abstract

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.

Abstract (in Czech)
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.

Abstract (in Czech)

Links
MSM0021622412, plan (intention)	Name: Interakce mezi chemickými látkami, prostředím a biologickými systémy a jejich důsledky na globální, regionální a lokální úrovni (INCHEMBIOL) (Acronym: INCHEMBIOL)
MSM0021622412, plan (intention)	Investor: Ministry of Education, Youth and Sports of the CR, Interactions among the chemicals, environment and biological systems and their consequences on the global, regional and local scales (INCHEMBIOL)