Policy making, strategic planning and management in general are complex decision making
tasks, where the formulation of a quantitative mathematical model may be difficult or …

Abstract Fuzzy Cognitive Maps (FCMs) are considered a soft computing technique
combining elements of fuzzy logic and recurrent neural networks. They found multiple …

This paper proposes a two-stage prediction model, for multivariate time series prediction
based on the efficient capabilities of evolutionary fuzzy cognitive maps (FCMs) enhanced by …

Time series appear in many scientific fields and are an important type of data. The use of
time series analysis techniques is an essential means of discovering the knowledge hidden …

Forecasting multivariate time series is an important problem considered in many real-world
scenarios. To deal with that problem, several forecasting models have already been …

Fuzzy cognitive map (FCM) is a soft computing methodology that allows to describe the
analyzed problem as a set of nodes (concepts) and connections (links) between them. In this …

This article is focused on the issue of learning of Fuzzy Cognitive Maps designed to model
and predict time series. The multi-step supervised-learning based-on-gradient methods as …

Fuzzy cognitive map (FCM) is a simple and user friendly tool for modeling complex systems.
It is described by the set of the concepts and the connections between them. FCM can be …

During the modeling of uncertain and imprecise systems, the intelligent approach, based on
the use of so-called Fuzzy Cognitive Maps (FCM) is often used. Constructors of the FCM …

Fuzzy cognitive maps (FCM) and Bayesian belief networks (BBN) are two of the most
frequently used causal knowledge frameworks for modelling, representing and reasoning …