Method of Fuzzy Parametric Selection for Making a Reasonable Decision by an Intelligent Training Module

Abstract

Selection of an optimal route within the intelligent approach provides for the possibility of applying soft models and computing in estimation of the trainee presence in the knowledge space. Among numerous ways of representation and processing of information of this type, the special place is held by those able to adapt to the maximal number of NO factors, characterizing the actual training situations, their measurable data and actual methods and ways of their processing that have ambiguities, uncertainties and incompleteness of the respective models and methods. In this paper, we suggest to extend the certain well-proven best practices in data analysis and transformation in the training environment information space to solving the actual training management problems. In addition, the paper demonstrates approaches to the use of Pareto-optimal approaches for fuzzy and underdetermined situations in actual training processes. Formally, this problem is solved with a fuzzy systemic graph. Variants of calculating procedures, allowing the use of the available apparatus of soft models and computing with the purpose to eliminate uncertainties when forming grounded decisions, are given. Methods and criteria of route options selection with regard of vaguely defined functional specification requirements have been developed pursuant to the study.