Neuroevolutional Methods for Decision Support Under Uncertainty

The article presents a comparative analysis of the fundamental neuroevolutional methods, which are widely applied for the intellectualization of the decision making support systems under uncertainty. Based on this analysis the new neuroevolutionary method is introduced. It is intended to modify both the topology and the parameters of the neural network, and not to impose additional constraints on the individual. The results of the experimental evaluation of the performance of the methods based on the series of benchmark tasks of adaptive control, classification and restoration of damaged data are carried out. As criteria of the methods evaluation the number of failures and the total number of evolution epochs are used

ОБРАБОТКА КОНТЕНТА В ИНФОРМАЦИОННЫХ СРЕДАХ НА ОСНОВЕ НЕЙРО-НЕЧЕТКОЙ МОДЕЛИ ПРИНЯТИЯ РЕШЕНИЙ

The article is devoted to the issues of mathematical modeling of the decision-making process of information content processing based on the fuzzy neural network TSK. Integral rating assessment of the content, which is necessary for taking a decision about its further usage, is made depended on varying characteristics. Mechanism for building individual trajectory and forming individual competence is provided to make the intellectual content search.Статья посвящена вопросам математического моделирования процесса принятия решения об обработке контента в информационных средах на основе нечеткой нейросети TSK. В зависимости от варьирующихся характеристик формируется интегрированная рейтинговая оценка контента, необходимая для принятия решения о его дальнейшем использовании. Для интеллектуализации поиска контента предложен механизм построения индивидуальной траектории и формирования индивидуальной компетенции

PROCESSING THE INFORMATION CONTENT ON THE BASIS OF FUZZY NEURAL MODEL OF DECISION MAKING

The article is devoted to the issues of mathematical modeling of the decision-making process of information content processing based on the fuzzy neural network TSK. Integral rating assessment of the content, which is necessary for taking a decision about its further usage, is made depended on varying characteristics. Mechanism for building individual trajectory and forming individual competence is provided to make the intellectual content search

INTELLECTUALIZATION OF OPEN EDUCATION SERVICES

The article presents the approach of leveling of the main drawbacks of online learning systems associated with diffi culties of objective monitoring of students’ knowledge. This method is based on the integration of the module that combines neural networks and genetic algorithms in the education system architecture with a goal of better examining of incomplete and inaccurate data. There are described the results of this method, which rises e-learning services to a new level of automation, agility and dynamism