Interval fuzzy modeling of complex systems under condіtіons of іnput data uncertaіnty

Abstract

expert knowledge about the subject area or inability to formalize them, as well as uncertainty caused by input feature space dimensionality (redundancy and noise) [1, 2]. All these factors are inherent in natural systems and processes in one way or another. As an example of modeling a system of this class, later in this paper we show how the condition of an artesian well can be evaluated at any given time from the beginning of hydrogeological exploration up to its full completion. This task is characterized by difficulties in accessing experimental data, since obtaining input data necessary for operation of any given model requires significant effort. It is therefore to be expected, that geological exploration which precedes putting an artesian well into operation lasts ranging from 6 months and up to several years [3].

Interval type-2 generalizing fuzzy model for monitoring the states of complex systems using expert knowledge

“…Як приклад успішного застосування інтервальних нечітких моделей, де експерти беруть участь у формуванні вхідного вектора параметрів, можна навести працю [8]. У ній показано особливості інтервального нечіткого моделювання на прикладі оцінювання стану артезіанської свердловини в довільний момент часу в межах від початку гідрогеологічної розвідки до її повного завершення.…”

A method of building type-2 fuzzy logic systems in multidimensional objects identification problems

“…Interval fuzzy set mathematics is used for modeling of complex systems under conditions of input data uncertainty in [19]. The results of the latter research are recommended for application in long-term natural processes study programs in order to shorten the time required for decision-making and to save cost during preliminary research in the hydrogeological exploration area.…”