This survey makes a review of the most recent applications and trends on fuzzy cognitive
maps (FCMs) over the past decade. FCMs are inference networks, using cyclic digraphs, for …

Fuzzy cognitive maps (FCMs) keep growing in popularity within the scientific community.
However, despite substantial advances in the theory and applications of FCMs, there is a …

Many studies on time series forecasting have employed fuzzy cognitive maps (FCMs).
However, it is required to develop techniques capable of effective responses and great …

In this paper, we present a neurodynamic approach to model predictive control (MPC) of
unknown nonlinear dynamical systems based on two recurrent neural networks (RNNs). The …

Among various soft computing approaches for time series forecasting, fuzzy cognitive maps
(FCMs) have shown remarkable results as a tool to model and analyze the dynamics of …

At the present, emotion is considered as a critical point of human behaviour, and thus it
should be embedded within the reasoning module when an intelligent system or a …

The challenging problem of complex systems modeling methods with learning capabilities
and characteristics that utilize existence knowledge and human experience is investigated …

Abstract Fuzzy Cognitive Maps (FCMs) are a graph-based methodology successfully
applied for knowledge representation of complex systems modelled through an interactive …

Abstract Fuzzy Cognitive Maps (FCM) are Recurrent Neural Networks that are used for
modeling complex dynamical systems using causal relations. Similarly to other recurrent …

Uncertainty and imprecision characterize human cognitive and reasoning processes. Fuzzy
cognitive maps (FCMs) are computationally simple yet effective structures to approximately …