USING GENETIC ALGORITHMS FOR BUILDING ADAPTIVE SUPPORT DECISION-MAKING IN ON THE BASISOF MODELS SITUATIONAL MANAGEMENT
Authors:
1.
Saint-Petersburg university of State fire service of EMERCOM of Russia
2.
Saint-Petersburg university of State fire service of EMERCOM of Russia
3.
Saint-Petersburg university of State fire service of EMERCOM of Russia
Type:
Article
Pages:
from 66
to 74
Status:
Published
Received:
12.12.2013
Accepted:
20.12.2013
Published:
25.12.2013
Language:
Russian
Keywords:
situational management, a scenario approach, the genetic algorithm, the elimination of emergency situations, the decision support system
Abstract (English):
This article discusses the possibility of building of adaptive decision support systems in case of absence of a priori information about the nature of emergency situations and its well-known scenario of liquidation. To solve this problem within the framework of situational management methods of are invited to consider the mechanism of genetic algorithms which enable heuristic way find an acceptable solution.
This article discusses the possibility of building of adaptive decision support systems in case of absence of a priori information about the nature of emergency situations and its well-known scenario of liquidation. To solve this problem within the framework of situational management methods of are invited to consider the mechanism of genetic algorithms which enable heuristic way find an acceptable solution.
Keywords:
situational management, a scenario approach, the genetic algorithm, the elimination of emergency situations, the decision support system
situational management, a scenario approach, the genetic algorithm, the elimination of emergency situations, the decision support system
1. Rutkovskaya D., Pilin'skiy M., Rutkovskiy L. Neyronnye seti, geneticheskie algoritmy i nechetkie sistemy / per. s pol'sk. I.D. Rudinskogo. M.: Goryachaya liniya-Telekom, 2006. 383 s.
2. Yah'eva G.E. Nechetkie mnozhestva i neyronnye seti. M.: BINOM, 2006.
3. Isaev S.A. Populyarno o geneticheskih algoritmah // Algoritmy. Metody. Ishodniki. URL: http://algolist.manual.ru/ai/ ga/ga1.php.
