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

MOOCs SHOULD LOOK TOWARDS EXPENDING ITS ADAPTABILITY

The article discusses the issues facing today’s growing and gaining momentum motion for the creation and implementation of massive open online courses. Special attention is paid to the ways to meet mass demand for higher education and proposes a new model of education based on a combination of existing achievements in the development and delivery of training courses the student with the automation of the processes themselves learning and assessment results

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

Professional competence of the person in the Smart-society

Now, there are processes of formation of a knowledge society – the Smart-society – are all the new features, which are characterized by obtaining a new effect from the use of information and communication technologies. The development of computers and communications creates the preconditions for moving the place of work out of the office space in the digital home. In these circumstances, more and more importance is given to the individual skills of the person, its ability to absorb a huge amount of diverse information, generate and innovate. Therefore, empowerment process for every professional who wants to be popular, it becomes continuous, becomes a constant need to learn and lifelong learning. In addition, requirements for the employees are changing, and the person must evaluate its relevance to society. This raises the question: how to evaluate the relevance? What is necessary for the Smart-society?What to learn or re-learn? Focus shifts from classical training to personal development. Traditional methods and approaches to learning have stopped covering the needs of the knowledge. Instead of selecting a limited number of the templates, each person is faced with the necessity to configure your own unique personality, to increasingly use informal learning, providing the individual development.The professional competence of the person in the Smart-society is formed in an interactive learning environment, using content from around the world, which is in the public domain. The assessment level of competence, identifying the need for professional development, early learning with the use of technology, provided by the Smart-education, are essential components of the formation process of professional competence of the person in the Smart-society. It is important to provide the compliance of the business metrics of employees to the content of the assessment test at the stage of internal validation for the purpose of timely identification of those competences, it is necessary to increase their level, and certification testing for confirming the level of professional competence of employees, which dictates the ethics of the Economy and Smart-society.This problem causes the need to use the active and relevant content. In order to solve the global task it is necessary to promote development and to use open educational resources. Such active approaches to learning increasingly spread, as the creation of professional communities, the use of cloud computing, mobile communication development.In the context of the professional standards’ implementation, the person should be prepared for such a certification and not pass it by trial and error. The person has to have a possibility to check and to develop the competencies. «Professional communities» can provide such a possibility, in our opinion. Professional community portal – is an effective tool for creating of the high quality and relevant content that can be used for the continuous development of competencies and the employers can submit their claims. Monitoring of competencies, including the monitoring in the centers of the qualification independent assessment should be carried out with the use of adaptive testing algorithms and test tasks continuously updated to meet the changing needs of the Smart-society

MODELING OF ELECTRONIC OPEN EDUCATIONAL RESOURCES

The article is devoted to modeling the process of creating open educational resources (OER). The technology of processing of the content presented in this paper provides solutions for the creation of competitive highquality e-learning courses, placed in an open information environment. The tools are analyzed in detail to create a virtual environment OER. The algorithm of the decision making process on the processing of contentbased neuro-fuzzy

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

INTEGRATED APPROACH TO THE ORGANIZATION OF ONLINE LEARNING IN THE MODERN UNIVERSITY

The article deals with the issues of an integrated approach to the organization of educational environment of the e-learning university. Proposes an approach that allows to store and maintain the knowledge generated in the learning process, to constantly improve not only educational material and keep it up to date, but also the very teaching methods, to make available e-learning courses for later use by other teachers

Machine Learning Ethics in the Context of Justice Intuition

The article considers the ethics of machine learning in connection with such categories of social philosophy as justice, conviction, value. The ethics of machine learning is presented as a special case of a mathematical model of a dilemma – whether it corresponds to the “learning” algorithm of the intuition of justice or not. It has been established that the use of machine learning for decision making has a prospect only within the limits of the intuition of justice field based on fair algorithms. It is proposed to determine the effectiveness of the decision, considering the ethical component and given ethical restrictions. The cyclical nature of the relationship between the algorithmic algorithms subprocesses in machine learning and the stages of conducting mining analysis projects using the CRISP methodology has been established. The value of ethical constraints for each of the algorithmic processes has been determined. The provisions of the Theory of System Restriction are applied to find a way to measure the effect of ethical restrictions on the “learning” algorith