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

In recent years fuzzy cognitive maps (FCM) have become an active research field due to
their capability for modeling complex systems. These recurrent neural models propagate an …

Abstract Fuzzy Cognitive Maps (FCM) may be defined as Recurrent Neural Networks that
allow causal reasoning. According to the transformation function used for updating the …

Abstract Fuzzy Cognitive Maps (FCMs) have been used to quantitatively model the
dynamics of complex systems and predict their behaviours. However, they are usually …

With a growing interest in Explainable Artificial Intelligence, the fuzzy cognitive maps (FCMs)
have proved to be a simple yet powerful tool for causal reasoning and decision making. It is …

In this paper, we address some shortcomings of Fuzzy Cognitive Maps (FCMs) in the context
of time series prediction. The transparent and comprehensive nature of FCMs provides …

During the last decade Fuzzy Cognitive Maps (FCM) have become a useful tool for solving
unstructured problems. In a few words they could be defined as Recurrent Neural Networks …

This paper discusses the challenge of modeling in-flight startle causality as a precursor to
enabling the development of suitable mitigating flight training paradigms. The article …

Fuzzy Cognitive Maps (FCMs) is a complex systems modeling technique which, due to its
unique advantages, has lately risen in popularity. They are based on graphs that represent …

Fuzzy cognitive maps (FCMs) are the best decision-making tools for making optimal
managerial decisions. This chapter introduces a focused decision-making model integrating …